leur eco-système. C’est l’une des raison pour lesquelles dans notre numéro, finalement très peu d’articles utilisent des big data (Bergström, 2018) : face aux restrictions qu’imposent les plateformes qui les contrôlent, des auteurs ont préféré avoir recours à des enquêtes de terrain classiques, seul moyen d’accéder à des informations crucales pour leurs études (Courmont, 2018; Kotras, 2018). Loin de représenter une tension entre sciences sociales d’une part et informatique de l’autre, l’utilisation encore limitée des grandes bases de données numériques dans nos disciplines résulte d’une forme de **privatisation des données** et de limitations d’accès (dont souffre d’ailleurs l’informatique dans la mesure où elle relève de la recherche publique). Afin de recueillir des témoignages divers tout en faisant apparaître des pistes pour avancer, nous avons proposé précisément cette question d’accès aux données dans la soirée de lancement du numéro que nous avons organisée à Sciences Po en décembre 2018, avec des représentants d’institutions différentes et de chercheur.e.s, en présence des auteurs du numéro.

## 5.2 Réseaux sociaux, éthique et recherche

Le mouvement général de **recul de la tolérance vis-à-vis des atteintes à la vie privée** des individus depuis quelques années (section 3.2), la **capture des données par des plateformes à des finalités commerciales** (section 5.1), et le flou légal sur nombre de questions liées aux données, posent de nouveaux défis éthiques et déontologiques aux chercheur.e.s. Ces enjeux sont **particulièrement aigus en analyse des réseaux sociaux** car même des efforts récents pour établir une base légale au scraping de données ont surtout visé la fouille de textes ou la recherche de contenus textuels, régies par le droit d’auteur et le principe de la liberté d’expression. Les données relationnelles qui intéressent les sociologues des réseaux sociaux ne sont pas du texte et n’entrent donc pas dans ce cadre, de sorte que les conditions de leur usage restent souvent indéfinies.

Ces freins s’ajoutent à des difficultés déjà bien connues en analyse des réseaux sociaux, comme l’impossibilité d’anonymat dans la collecte des données, difficulté à recueillir le consentement des *alter* nommés par un *ego* dans une enquête avec générateurs de noms (Breiger, 2005). Il y a aussi des défis plus récents résultant de la diffusion des réseaux socio-numériques et de la **sur-valorisation de la connectivité** qui peuvent gêner les enquêtés, susciter des réponses biaisées, ou rendre la restitution délicate dans la mesure où les résultats d’une recherche peuvent être mal interprétés (section 4.1).

Au titre du groupe BSA-SNAG (sous-section 2.5), j’ai souhaité lancer une réflexion à ce sujet. Avec A. D’Angelo (Université de Nottingham), L. Ryan (Université de Sheffield) et A.A. Casilli (Telecom Paris), j’ai organisé un atelier sur « *Recent Ethical Challenges in Social Network Analysis* » (RECSNA), qui s’est tenu à l’Institut d’Études Avancés de Paris en décembre 2017, avec un financement de la Maison des Sciences de l’Homme Paris-Saclay. En plus de la BSA, se sont associés à l’organisation de l’événement le groupe ENDL (sous-section 2.6) et le Réseau Thé-
Crozier, M. & E. Friedberg. 2014, *L'acteur et le système : Les contraintes de l'action collective*, Seuil, 1ère édition 1977.

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matique « Réseaux Sociaux » de l'Association Française de Sociologie (coordonné à l'époque par G. Favre, Université de Toulouse Jean Jaurès, et E. Penalva-Icher, Université Paris-Dauphine).

L'intérêt qu'a suscité cette thématique nous a ensuite amené à monter un projet de numéro spécial sur ce même sujet de la revue *Social Networks*, la plus importante dans le domaine de l'analyse des réseaux sociaux. Des 17 pré-propositions initialement reçues, 1 a été déjà acceptée et 8 sont en révision au moment où j'écris ces lignes. Il y aura aussi une longue introduction par les coordinateurs du numéro et une post-face du Prof. R. Breiger, coordinateur d'un précédent numéro de la même revue sur l'éthique de la recherche sur les réseaux sociaux (2005). La date de la publication définitive du numéro n'est pas encore établie (2020 ou 2021).

Ces questions m'amènent au dernier point que je souhaite aborder, la réflexion que je mène sur l'articulation entre recherche et société et « l'impact » sociétal de mes travaux.

# 6 Une recherche d'impact

Toute recherche scientifique, et la mienne ne fait pas exception, est tiraillée entre une exigence d'abstraction d'un côté, et d'impact concret de l'autre. Si la première répond directement au besoin de faire progresser la connaissance, la dernière légitime notre rôle dans la société. Tous nos choix (d'objet de recherche, de problématique, et même de contexte empirique, par exemple en termes de temps et de lieu d'une étude) peuvent avoir des effets sur l'être humain, la vie associée ou l'environnement. Le cas des sciences humaines et sociales est particulièrement délicat, le/la chercheur.e étant immergé.e dans la réalité humaine et sociale qu'il/elle étudie. J'ai toujours prêté beaucoup d'attention à cette dimension de ma recherche, et il me semble important d'y revenir avant de conclure, en proposant une lecture quelque peu différente des projets dont il a été question plus haut.

Dans ce qui suit, j'utilise te terme « impact » qui sans être parfait, dispose d'une définition claire qui peut constituer un ancrage pour la discussion. J'interprète cette notion aux sens du REF (Research Excellence Framework), le système britannique d'évaluation de la recherche, pour lequel il s'agit de **tout effet, changement ou bénéfice que la recherche apporte à l'économie, la société, la culture, la politique publique, les services, la santé, l'environnement ou la qualité de la vie** <fnref n="7" />.
On parle également d'impact lorsque l'effet de la recherche est la réduction ou la prévention de dommages, risques, coûts, ou autres effets négatifs.

Cette définition d'impact va au delà de la notoriété scientifique et même de la présence dans la presse ou dans les débats publics. Tout travail de recherche ne peut pas

<footnote n="7">7. L'effet, changement ou bénéfice peut concerner des activités, des attitudes, des prises de conscience, des comportements, des capacités, des opportunités, des performances, des politiques, des pratiques, des procès ou leur compréhension. Le destinataire peut être une audience, un bénéficiaire, une collectivité, une organisation ou des individus, quelle que soit leur localisation géographique, nationale ou internationale.</footnote>
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Lance Bennett, W. & A. Segerberg. 2013, *The Logic of Connective Action. Digital Media and the Personalization of Contentious Politics*, Cambridge University Press.

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prétendre à toucher la société de la même manière, et le mien n'y est pas non plus
toujours arrivé. La just-in-time sociology que j'ai essayé de prôner en 2011 avec
A.A. Casilli (Télécom Paris), lors de la réalisation de notre recherche sur les émeutes
londoniennes de l'été (projet ICCU, sous-section 2.5) voulait affirmer la possibilité,
pour la sociologie, de répondre rapidement à une demande émanant des pou-
voirs publics et ne pouvant pas attendre les délais habituels de la recherche.
En l'occurrence, nous avons réalisé une étude par modélisation multi-agents de la
possibilité que la censure d'internet, évoquée (mais finalement non mise en œuvre)
par le gouvernement britannique, parvienne à son objectif d'arrêter les violences.
Notre modèle très simple, concocté et publié en ligne en 48 heures, répondait par la
négative (Casilli & Tubaro, 2012). Cette démarche permet de se faire une place dans
les débats, en utilisant les technologies numériques pour faire connaître très vite les
résultats obtenus et pour s'engager dans une discussion avec les parties prenantes.
Elle avait dans l'immédiat enthousiasmé des collègues, et un atelier sur just-in-time
sociology a été organisé à l'EPFL de Lausanne en décembre 2012, où j'ai été in-
vitée comme keynote speaker. La presse en avait également pris connaissance, et
j'ai eu l'opportunité d'enregistrer une émission de 15 minutes pour la BBC Radio
3, où je présentais mes résultats et les commentais (2012). Mais comme cela nous a
été à juste titre reproché, cette démarche ne donne pas le temps d'approfondir et de
prendre de la hauteur (Vinck, 2016). Avec le recul, nous ne sommes pas parvenus à
mettre en œuvre un véritable changement social au delà de ces quelques débats, et le
projet n'a pas pu avoir une suite qui l'inscrive dans la durée, faute de financements.

En revanche, le projet ANAMIA (sous-section 3.3) a produit un véritable change-
ment, et ce même au delà de sa date officielle de clôture en 2013. Le projet de loi de
modernisation du système de santé, proposé par le gouvernement français en 2015,
incluait un article punissant les auteurs de contenus « pro-ana » avec la prison et une
amende. Une proposition de loi semblable était en discussion au Parlement italien
depuis l'été 2014. Ces propositions allaient à l'encontre des résultats de l'étude, et
posaient de manière concrète la question de l'impact et des objectifs de la recherche
scientifique : fallait-il simplement se consacrer à la publication d'articles dans des
revues savantes en ignorant la situation concrète, ou s'investir dans un débat public
où nous n'étions pas invités ? Il devenait impossible d'aspirer à une « neutralité » de
la recherche comme séparation nette entre savoir et politique, car tout choix aurait
eu des conséquences : s'exprimer aurait pu faire changer la loi, se taire aurait pu, à
l'inverse, en faciliter le parcours. Le choix fait en concertation avec les membres de
l'équipe ANAMIA a été d'interpréter le principe de neutralité comme un devoir de
ne pas déformer les faits, tout en soulignant l'importance d'en révéler les présup-
posés, les contours et les conséquences (Casilli & Tubaro, 2016; Tubaro, 2017). Il
s'agissait de sensibiliser les politiques et l'opinion publique aux risques des mesures
punitives proposées, qui ne s'attaquaient pas au véritables sources du problème et
qui auraient pu produire des effets négatifs en repoussant ces sites vers des zones
plus obscures du web. Nous avons ainsi pris la parole publiquement, notamment
dans une tribune collective dans Libération le 2 avril 2015, plusieurs interviews dans
la presse, et des actions de sensibilisation envers les élus (j'ai personnellement été
reçue par une sénatrice), les professionnels de santé (Fédération Française Anorexie
& M. Van Alstyne. 2009, «Computational social science», *Science*, vol. 323, n° 5915, p. 721-723.

Le Ludec, C., P. Tubaro & A. A. Casilli. 2019a, «Combien de personnes micro-travaillent en France ? Estimer l’ampleur d’une nouvelle forme de travail», *Document de travail i3 19-SES-02*.

Le Ludec, C., P. Tubaro & A. A. Casilli. 2019b, «How many people microwork in France ? Estimating the size of a new labor force», *arxiv 1901.03889*.

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Boulimie, FFAB, appelée AFDAS-TCA à l'époque) et les associations (Fédération Nationale des Associations liées aux Conduites Alimentaires, FNA-TCA). J'ai été intervenante dans des journées et autres événements organisés par ces associations (Paris, janvier, mai, octobre 2015). En parallèle, j'ai mené une action analogue en Italie, où j'ai été invitée à intervenir à plusieurs congrès des professionnels et des associations (Pise, octobre 2014; Parme, novembre 2014; Venise, mai 2015).

<figure><img src="image_11.png" /><figcaption>**Fig. 9** Infographie produite pour la restitution au grand public des principaux résultats du projet ANAMIA. Source : projet ANAMIA.</figcaption></figure>

Au final, aucune de ces mesures punitives n'a abouti : en automne 2015, la pro-
position italienne était retirée, et l'article français supprimé. Le texte définitif de la
loi sur le système de santé n'en conserve plus de trace. ANAMIA est explicitement
citée comme une raison de ce choix dans le compte rendu de la séance de l'As-
semblée nationale qui valida la version finale de la loi. Il s'agit d'un véritable
impact aux sens du REF : Une recherche sociologique a ainsi réussi à participer à la
transformation du monde qui l'entoure. L'exercice d'ANAMIA a renversé la logique
du just-in-time sociology, replaçant la recherche dans la longue durée mais s'ouvrant
dès le départ à une implication citoyenne. Elle suggère la possibilité d'une action
de la sociologie sur le monde qui ne renonce pas aux critères de recul critique
qui définissent l'identité de la discipline.

Le terrain d'enquête *Sharing Networks* (sous-section 4.1) a été préparé par et
suivi de, **nombreuses rencontres de restitution, d'échange et de confrontation
avec les membres de OuiShare.** Leur enthousiasme pour mes résultats a de loin
dépassé mes attentes : les graphes que j'avais produits pour représenter les réseaux
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Scholz, T. 2016, *Platform Cooperativism : Challenging the Sharing Economy*, Rosa Luxemburg Stiftung.

Scholz, T. & N. Schneider. 2017, *Ours to Hack and to Own : The Rise of Platform Cooperativism : A New Vision for the Future of Work and a Fairer Internet*, OR Books.

Schor, J. 2017, «Does the sharing economy increase inequality within the eighty percent? Findings from a qualitative study of platform providers», *Cambridge Journal of Regions, Economy and Society*, vol. 10, n° 2, p. 263-279.

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Strubell, E., A. Ganesh & A. McCallum. 2019, «Energy and policy considerations for deep learning in NLP», *CoRR*, vol. abs/1906.02243.

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de relations formés au OuiShare Fest de 2016 sont devenus une gif animée qu'ils sont largement diffusée en ligne, et ont même été imprimés sur des T-shirt que deux membres portaient l'année suivante (figure 10). Ils se sentaient valorisés par la capacité de leur événement à mettre en relation les participants, que mes graphes faisaient apparaître, en distinguant un « avant » fait de relations éparses et un « après » où elles se densifient.

<figure><img src="image_12.png" /><figcaption>**Fig. 10** Les T-shirt imprimés et portés par des représentants de OuiShare en 2017, représentant les graphiques que j'avais produits avec les données collectées lors de l'événement de 2016. *Before* = relations pre-existentes, *After* = relations formées lors de l'événement. Source : projet *Sharing Networks*.</figcaption></figure>

Les membres de OuiShare ont vu mon travail comme **une évaluation** de leur événement, qu'ils jugeaient utile mais qu'ils n'avaient pas les ressources pour réaliser en interne. Ils ont été aussi intéressés par les résultats sur la capacité du Fest à intégrer les femmes – un point sur lequel j'ai été interviewée pour leur service radio interne en 2018, et qui les a amenés à réflechir aux facteurs qui, dans l'événementiel, peuvent jouer dans l'obtention de ce résultat. Il s'agit, là aussi, d'une forme d'impact au sens du REF, dans la mesure où mon travail a aidé une organisation à mieux comprendre des aspects de son activité et à s'engager dans une réflexion visant à les systématiser et les diffuser. Ce n'est pas, pour autant, un exercice sans risques, dans la mesure où l'appropriation des résultats d'une recherche publique par les parties prenantes peut les détourner et, sous certaines conditions (qui ne se sont heureusement
Tubaro, P. 2018a, «Emergent relational structures at a “sharing economy” festival», dans *Proceedings of the 7th International Conference on Complex Networks and Their Applications*, vol. 2, édité par L. Aiello, C. Cherifi, H. Cherifi, R. Lambiotte, P. Lió & L. Rocha, p. 559–571.

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ment pas présentées dans mon cas) les utiliser à l'avantage de certains groupes et
au détriment d'autres. Cette expérience m'a conduite à une réflexion profonde sur
les enjeux de la restitution aux acteurs de terrain, que je suis en train de développer
dans un article soumis pour le numéro spécial de *Social Networks* sur l'éthique de
la recherche, que je coordonne (sous-section 5.2).

L'étude DiPLab (sous-section 4.2) est également une occasion d'engagement pub-
blic dans la mesure où nous avons choisi de nous faire financer par des décideurs
publics (France Stratégie, un service du Premier Ministre), des organismes syndi-
caux (Force Ouvrière, IRES) et des acteurs privés (Foule Factory) qui souhaitent
pouvoir dégager, à partir de nos résultats empiriques, **des lignes-guides visant à**
**promouvoir des formes équitables et éthiques d'organisation du travail sur les**
**plateformes numériques.** Le travail de construction de préconisations de politiques
est encore en cours, et nous le menons en collaboration avec ces divers acteurs. Il
est donc encore trop tôt pour se prononcer sur un véritable impact. Mais l'effort
de communication que nous avons entrepris est d'ores et déjà en train de produire
quelques premiers effets, ne serait-ce qu'en **mettant la question du micro-travail**
**à l'ordre du jour.** Le rapport conclusif du projet a été diffusé en ligne en mai 2019,
et une journée de restitution pour le grand public a eu lieu dans les locaux de France
Stratégie le 13 juin 2019, attirant environ 250 participants issus surtout des adminis-
trations publiques, mais aussi des entreprises de technologie, des syndicats et de la
presse. Les résultats ont été repris dans plusieurs médias (BBC World Service, Radio
France Inter, Le monde, Le journal du CNRS, Agence France Presse, La Tribune,
Les Echos, La Croix, Alternatives Economiques, etc.). Si à elle seule, la visibilité
médiatique n'est pas du véritable impact, elle a ici eu l'effet de changer les termes
du débat public sur le travail des plateformes. Limité jusqu'ici aux cas des livreurs
Deliveroo et des chauffeurs Uber, il s'est étendu au micro-travail – qui a des caracté-
ristiques différentes qui n'étaient guère prises en compte auparavant, et qui comme
je l'ai évoqué plus haut, met en relation le débat sur les conditions de travail et le
rôle des plateformes d'une part, et l'intelligence artificielle de l'autre. Un change-
ment du débat public – et donc potentiellement, du moins à terme, des priorités de
la politique publique – est déjà une forme d'impact.
<figure><img src="image_4.png" /></figure>
<figure><img src="image_13.png" /><figcaption>**Fig. 11** La journée de restitution du projet DiPLab chez France Stratégie, 13 juin 2019. Source : France Stratégie.</figcaption></figure>

Cet exercice n'est pas facile, et je l'aborde en déployant le concept de **double vulnérabilité** de Chardel (2013) : une vulnérabilité des sujets d'étude en raison de leurs risques de santé (ANAMIA) ou de leurs conditions de travail précaires (DiPLab), mais aussi le risque que courent les chercheur.e.s en les prenant en charge, et qui peut s'élargir aux défis d'ordre éthique, politique et scientifique auxquels ils/elles font face, au milieu de conflits qu'ils/elles ne maîtrisent qu'incomplètement. Col laborer avec des acteurs gouvernementaux ou syndicaux n'est pas toujours simple, les objectifs, les points de vue et les pratiques n'étant pas les mêmes, de sorte que les chercheur.e.s peuvent finalement se trouver à légitimer des actions dont ils/elles connaissent les imperfections. Le travail avec les gérants des plateformes peut être encore plus délicat, dans la mesure où les intérêts privés peuvent entrer en conflit avec des objectifs sociaux – une situation bien connue dans le monde des associations sans but lucratif, ici poussée à l'extrême. Jusqu'ici, la prise de conscience de cette vulnérabilité m'a aidé à gérer les limites de la connaissance que je peux produire et des actions qui peuvent en être issues.

## 7 Projets d'encadrement

Les trois thèses que j'ai encadrées (sous-section 2.5) jusqu'ici portaient sur des thèmes d'analyse des réseaux organisationnels pour ainsi dire classiques : la collaboration et concurrence des entreprises privées dans le secteur mondialisé de l'eau (Y. Sarabi, Univ. Greenwich, 2013-2017), les effets de spillover des efforts de R&D des entreprises (H. Minh Luong, Univ. Greenwich, co-direction avec M. Ugur, 2014-
Disembedded or deeply embedded?

Toward a multi-level network analysis approach
of the online platform economy

Paola Tubaro

Abstract

This paper extends the economic-sociological concept of embeddedness to en-
compass not only social networks of, for example, friendship or kinship ties, but also
economic networks of ownership and control relationships. Applying these ideas to
a case study of digital platform labor pinpoints two possible scenarios. When plat-
forms take the role of market intermediaries, economic ties are thin and workers are
left to their own devices, in a form of “disembeddedness”. When platforms are parts
of intricate inter-firm outsourcing structures, however, economic ties envelop work-
ers in a “deep embeddedness” which involves both stronger constrains and higher
rewards. The discovery of deep embeddedness brings to light the far-reaching social
implications of platform business models that were previously under-researched.
More generally, it enriches the notion of embeddedness and reinforces its capacity
to account for actors’ position in today’s globalized, highly specialized production
system.

**Key words:** Digital labor, embeddedness, outsourcing, multi-level network analysis, platform economy, transaction costs

# 1 Introduction: embeddedness in markets, firms and platforms

Embeddedness, or the idea that economic action is grounded in social structures, has been a founding block of economic sociology for the past few decades. In a path-breaking article, Granovetter (1985) contended that people do not act as atoms in an impersonal market, nor do they passively internalize outside norms: rather, their behaviors result from the history of their relationships and from their positions

Laboratoire de Recherche en Informatique, Centre National de la Recherche Scientifique, Paris
Saclay, e-mail: paola.tubaro@lri.fr
2018), les effets des échanges sur la performance des hôpitaux (A. Piazza, Univ. Greenwich, co-direction avec F. Pallotti, 2014-2019). Certains mémoires de master (sous-section 2.6) ont suivi cette même voie, notamment avec l'étude des réseaux géographiques des travailleurs en déplacement (N. Salez, ENSAE, 2019), d'autres se sont davantage penchés sur les enjeux des réseaux socio-numériques, comme les femmes dans l'économie collaborative (A. Papp, ENSAE, 2019), la gouvernance des communautés en ligne (M. Cornet, EHESS, 2017), les débats politiques sur Twitter (P. Cochet, ENSAE, 2019; E. Koba, ENSAE, 2018; G. Stephan, EHESS, 2017), l'émergence et diffusion de tendances sur les réseaux en ligne (J. Lévy, EHESS, 2019), etc. Les stagiaires que j'ai encadrés, de niveau L3, M1 et M2, étaient davantage subordonnés aux besoins de ma propre recherche, notamment pour les projets *Sharing Networks* (S. Benmarhnia 2017, C. Oster 2017, S. Sinz 2017, E. Wong 2018), RESTO (J. Posada 2017), et DiPLab (M. Besenval 2018, N. Sapkota 2019).

Dans le cadre du projet ANR *The HUman Supply cHain behind smart technologies* (HUSH, avec A.A. Casilli et U. Laitenberger, Telecom Paris), qui débute cet automne et qui constitue un prolongement des recherches entamées avec DiPLab (sous-section 4.2), je vais diriger la thèse d'un.e doctorant.e en sociologie qui étudiera la clientèle du micro-travail des plateformes, surtout les start-ups et autres petites entreprises productrices et/ou utilisatrices de solutions d'intelligence artificielle. Il s'agit de lever un important verrou scientifique, la littérature encore limitée sur le micro-travail s'étant surtout intéressée à l'offre de travail, laissant dans l'ombre la demande. Cette thèse exigera une prise en compte approfondie des exigences et des besoins de l'intelligence artificielle, et sera donc menée dans un contexte interdisciplinaire, au sein du Laboratoire de Recherche en Informatique dont je suis membre.

Au sein de ce même projet, je co-encadrerai deux autres thèses. L'une d'entre elles, dont le directeur principal est A.A. Casilli, portera sur les chaînes de sous-traitance du micro-travail qui s'étendent de la France vers les pays francophones d'Afrique. L'autre, dont le directeur principal est U. Laitenberger, adoptera une approche davantage économique / économétrique pour documenter le fonctionnement de plateformes de micro-travail et le mettre en relation avec la conjoncture économique locale et globale.

D'autres projets de thèses que je pourrai encadrer par la suite approfondiraient des aspects encore peu explorés de la société des plateformes, comme le devenir de l'économie collaborative après les premiers enthousiasmes et les déceptions qui les ont suivis (sous-section 4.1), l'évolution des modèles d'affaires et leurs conséquences sur le travail, les usages et la consommation (prolongeant ainsi le travail récemment entamé dans le projet BOBCAT (sous-section 4.2). Des thèmes sur lesquels j'aimerais faire travailler des étudiants sont les coûts environnementaux outre que sociaux du numérique (et en particulier, de l'intelligence artificielle), et les inégalités d'accès aux données comme ressource productive, et les clivages qu'elles établissent, d'un côté entre les établissements publics et privés, et de l'autre côté, au sein du secteur privé, entre petites/moyennes et grandes entreprises.
with respect to other relationships. Granovetter explicitly suggested to operational-
ize embeddedness through *networks* of social relationships, although he did not
use graph-theoretic formalisms in his article. Soon afterwards, advances in theory
(for example, Burt (1992)) and analytical techniques (Wasserman and Faust, 1994)
firmly established social network analysis at the heart of embeddedness scholarship.
Since then, a rich empirical literature has shown that, for example, firms form part-
nerships based on their networks of prior alliances (Gulati and Gargiulo, 1999), that
long-term personal relationships help companies to face the highs and lows of the
market (Uzzi, 1996, 1997), and that friendship among managers dampens the worst
effects of price competition (Ingram and Roberts, 2000).

This – still growing – current of research has deployed the construct of the net-
work in manifold variants and combinations. But overall, network ties are of two
main types: when internal to the boundaries of the firm, they serve to explain how
this firm works – who gains knowledge or power internally, or how consensus forms
around a decision. When they cross firm boundaries, ties are channels for market re-
lationships – whether competitive or oligopolistic, global or local, trusted/repeated
or “arm’s length” (Uzzi, 1997). Put differently, economic sociology implicitly in-
herit a vision à la Ronald Coase (1937) that identifies the firm and the market as
two alternative, albeit possibly coexisting, devices for economic coordination.

Rooted in transaction cost economics (Coase, 1937; Williamson, 1975, 1981) the firm-market duality is admittedly not an indigenous concept to sociology. Rather than framing problems as referring to firms vis-à-vis markets, economic sociologists tend to use the language of organizations more generally: for example, they characterize networks as intra- or inter-organizational. Sociology and transaction cost theory converge in recognizing that economic activity requires some degree of organization to avoid chaos: there must be a system for matching actors, spreading information, arranging resources, dividing up the work. Even the market is not the impersonal, automated and cost-free mechanism that neoclassical economics imagined, but rather needs rules, intermediaries and support services (Favereau and Lazega, 2002). Against this common ground, there is still value in explicitly separating markets from firms, because they elicit different types of costs from actors, with distinct effects on their actions. In markets, there can be search costs, bargaining/decision costs, and policing/enforcement costs, while in firms, there are costs of planning, of assigning activities to individuals, of grouping activities into divisions, of controlling results and of delegating authority. Carruthers and Uzzi (2000) claim that within sociology, the study of the firm has started earlier, and progressed faster, than the study of the market.

This distinction becomes all the more relevant today, as the rise of digital plat-
forms (Gawer, 2009; Srnicek, 2016) has been saluted by many as a third way
in which coordination may occur, beyond the firm and the market (Sundararajan,
2016). While this characterization is subject to discussion, it nevertheless challenges
the practices of economic sociologists and their underlying conceptualizations: can
the notion of embeddedness and its common operationalization through social net-
work analysis be easily transposed to the world of the digital platform? If not, what
is that does not fit, and what aspects of our thinking should change?
Méthodologiquement, j’ invite mes étudiants à mobiliser des techniques parmi
les plus avancées en sciences sociales afin de bien distinguer et caractériser la
complexité des processus sociaux investis dans tout projet de recherche ambitieux.
L’ analyse des réseaux était un instrument traditionnellement utilisé pour opération-
naliser les concepts de la sociologie des organisations ; elle peut être enrichie, d’une
part par des techniques de modélisation (modélisation stochastique orientée acteur,
modélisation et simulation multi-agents), de l’autre par une extension au traitement
des grandes masses de données qui sont consubstantielles au fonctionnement d’in-
ternet, y compris avec le machine learning. L’ usage de ces méthodes n’est pas pour
autant une fin en soi, et prend tout son sens dans le cadre d’une articulation d’ instru-
ments, techniques et outils qui, ensemble, peuvent nourrir une recherche même très
complexe. Il faut en particulier enrichir toute analyse par une compréhension fine
du contenu et du sens des actions ou interactions, ce qui ne peut se faire qu’ avec des
instruments d’enquête classiques, quantitatifs et qualitatifs.
These questions are obviously of practical importance for scholars of the plat-
form economy, who may need to adapt existing theoretical constructs to the speci-
ficity of their object. They are also of broader theoretical importance insofar as they
re-open the question of whether the notion of embeddedness, as shaped by Gra-
novetter's influential article, really succeeds in integrating the economy and society.
Critics did not much question the capacity of today's embeddedness research to
shed light on the firm, but were dissatisfied with its representation of the market.
Calnitsky (2014) and Krippner (2002) claim that economic sociology still follows
neoclassical economics in presupposing the existence of a core asocial market which
uncomfortably sits surrounded by society. If we further stretch this concept to de-
scribe the platform, will we uncover other implications of it that have remained
dormant so far?

As a first step toward answering these questions, I propose a view of platforms that benefits simultaneously from recent theoretical developments in economics and in economic sociology. I use insight from transaction cost theory (and, to a lesser extent, two-sided market models) within economics, and from the “multi-level analysis of networks” applied to economic sociology. For tractability and to ensure comparison with recent literature (Wood et al., 2019b), I narrow down my analysis to the case of online labor, where digital platforms allocate tasks and jobs to providers who execute them remotely from their laptops or smartphones.

In this setting, I show that the common interpretation of Granovetter’s embed-
dedness in terms of *social* networks of individuals – peers, friends, relatives – is
limiting. Drawing on the multi-level approach proposed by Brailly et al. (2016), I
extend the concept of embeddedness to also encompass *economic* networks, which
include combinations of firm-to-firm and individual-to-firm networks. Their jux-
taposition brings to light the linkages between platforms’ business models, their
structure of commercial ties, and workers’ individual outcomes. Two configurations
can be observed on this basis: when platforms take the role of mere market inter-
mediaries that connect workers and clients, economic ties are weak regardless of
social ties, and workers are left to their own devices, in a form of *disembeddedness*.
When platforms take on management roles akin to firms, economic ties take highly
complex forms with multiple layers of contractors, brokers and suppliers that frame
the activity of the individual. These layers constitute a structure that is evocatively
reminiscent of complex neural networks in so-called “deep learning”, and I thus
propose the notion of “*deep embeddedness*” to describe them.

The discovery of deep embeddedness has three main implications for research in economic sociology. Substantively, it contributes to the empirical literature on the platform economy by describing the business models of some online labor platforms that have remained largely under-researched so far. Epistemologically, it demonstrates the value of dialogue between sociology, social network analysis and parts of economics, under an organizational umbrella. Theoretically, it indicates that the relationships that matter are not only personal ones such as friendship or kinship, but also economic ones – relations that describe who owns which hardware and software tools, who recruits workers, who provides quality controls. Augmented to include more diverse sets of relationships, Granovetter’s original intuition is capable of syn-
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## 2 Conceptions of embeddedness: from Polanyi to Granovetter and beyond

The concept of embeddedness is not an easy one to define. Long before Granovetter (1985), its origins are attributed to the highly influential work of Karl Polanyi (1944) where it took a broader, more comprehensive meaning. According to Beckert (2009), it encompassed the limits that institutions and the moral fabric of society impose on economic transactions, while also alluding to the normative task of stabilizing the organization of society through the institutional regulation of the economy. However, Polanyi's formulation is confusing, not least because he used the term only twice in his book, although the concept underpins his overall view. Peck (2013) identifies a sharp contradiction, whereby Polanyi argued in some places that all economic activity is always “embedded and enmeshed in institutions economic and noneconomic” (Polanyi, 1957), but proposed a more radical view elsewhere, with focus on the disembedding of the “fictitious commodities” of labor, land and money and the importance of societal-level legal, normative and cultural constraints that limit commodification. Peck (2013) refers to the former as “soft Polanyi” and to the latter as “hard Polanyi”. In this perspective, the work of Granovetter (1985) is a development of the soft Polanyi that leaves aside the hard version<fnref n="1" />.

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ors to explain network structures, as a complement to already existing “network theory” that uses networks to explain behaviors (Borgatti and Halgin, 2011). There is growing interest in the content and meaning of ties, notably through qualitative and mixed-method network analyses (Crossley, 2010; Dominguez and Hollstein, 2014). A research program in “neo-structural sociology” combines structure, culture, and agency (individual and collective) in new ways to study contemporary economies (Lazega, 2018).

Specifically on embeddedness, a step forward is the re-framing of the concept as a multi-level problem. Recognizing that most extant research separates the analysis of networks between firms and analysis of networks between individuals, Brailly et al. (2016) propose to study them jointly, each constituting a level in a multi-level analysis (Snijders and Bosker, 1999). In practice, they consider at the same time the networks of inter-individual ties *I* — *I*, the network of inter-firm ties *F* — *F*, and the affiliation network (à la Breiger (1974)) that links individuals to firms *I* — *F*. The first two, within-level networks may be characterized as “horizontal”, and the third one, across levels, as “vertical”, as illustrated schematically in figure 1. Brailly et al. (2016) show that while each level has its own specific processes, they are partly nested and a full understanding must take into account their inter-dependencies. Published in a social network analysis journal, these ideas still wait to be fully recognized within sociology. They suggest a way in which networks reconcile the social and the economic, which correspond to different levels: the horizontal networks between individuals *I* — *I* are typically social (friendship, advice, information exchange) while those between firms *F* — *F* are economic (contracts, alliances) and the vertical networks that tie individuals to firms *I* — *F* are also economic (mostly employment relationships, though sometimes they may take other forms such as appointments to board directorships). But then, can a multi-level approach that combines all of these respond to (at least some of) the criticisms addressed to Granovetter’s concept of embeddedness? Does it suffice to take on board the insights that readers found in Polanyi, but not in the Granovetterian tradition?

This brief overview summarizes aspects of the debates surrounding embeddedness that are of relevance to better understand how digital platforms are changing the current socio-economic landscape. While network structures are crucial to operationalize embeddedness, most discussions revolve around the nature and meaning of these networks (whom they connect, what relationships they represent), as well as their structures and types (within and across levels, or horizontally and vertically). If these ideas are (more or less) well-positioned to improve the capacity of the embeddedness concept to enlighten its original objects of study, the firm and the market, how do they perform with regard to platforms?

## 3 A case study: Platforms for online labor

In essence, platforms are coordination devices based on use of digital technologies. The engineering literature defines them as extensible hardware or software func-
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<figure><img src="image_5.png" /><figcaption>**Fig. 1** A schematic graph representation of multi-level embeddedness. Nodes are actors (cyan circles = individuals, black squares = firms) and lines are ties between actors (black = inter-firm ties *F* − *F*, cyan = inter-individual ties *I* − *I*, gray = individual-firm ties *I* − *F*). Source: author's elaboration, adapted from Brailly et al. (2016).</figcaption></figure>

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## 3.1 Digital platforms and embeddedness

As technology-enabled coordination devices, internet platforms interrogate extant understandings of embeddedness in two main ways. First, they challenge the established distinction between firm and market as devices for economic coordination (Sundararajan, 2016, pp. 78-79). Are they just another instance of firms or of markets, a hybrid, or an entirely new third way? Is their alleged capacity to reduce transaction costs (Lobel, 2018) enough to supersede the firm in favor of the price mechanism (or vice-versa)? It is difficult to answer these questions, owing to lack of shared definitions and widespread use of the everyday-language meaning of the terms “firm” and “market” – not least because different disciplines take part in the debate, each with its own vocabulary.

Perhaps in no other area is ambiguity more apparent than in the inter-mediation of *labor* – where even greater theoretical rigor might bring little improvement, if we believe with Coase (1937, p. 392) that labor services are most relevant to determine the arbitrage between firm and market, all other production inputs being far easier to accommodate into existing theories. Labor platforms are those that bring together clients and workers to buy and sell “gigs”. Because these workers are recruited on demand and their commitment ends as soon as their output is delivered, they are legally not employees. But because they rarely have the freedom to shape and manage their work, they are not fully independent providers either. Labor platforms blur the economic firm-market duality as much as the legal notion of an employer-employee relationship (De Stefano, 2016; De Stefano and Aloisi, 2018).

Second, platforms transform relational mechanisms such as reciprocity and trust, that the embeddedness literature thought to support economic action. When they reached center-stage in the early 2010s, and were surrounded by enthusiasms around the promises of “collaborative” consumption (Botsman and Rogers, 2010) and a “sharing” economy (Lessig, 2008), platforms seemed to elevate these mechanisms from informal to formal (and valuable). But it soon turned out that platforms replace these social mechanisms with impersonal systems of reputation-monitoring (Wood et al., 2019a) which impose discipline and are akin to surveillance. Again, this tension is particularly apparent in labor platforms, whose algorithmic infrastructure records workers’ activities and transforms them into publicly-visible performance scores (Rosenblat, 2018). These systems arouse strategic reactions on both sides and call for caution before interpreting any observations.

On this basis, I contend that labor platforms are an ideal arena to study the present transformations of embeddedness. But even so, they constitute a very broad object of study encompassing heterogeneous cases. In what follows, I review extant categorizations to identify particularly relevant sub-groups.
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## 3.2 Online labor platforms

Existing efforts to draw typologies of labor platforms (Codagnone et al., 2016; Howcroft and Bergvall-Kåreborn, 2019; Schmidt, 2017), share two common criteria even though not always expressed in the same terminology. One is the extent to which work is performed offline while inter-mediation occurs online, in comparison to all-online labor platforms. The former category encompasses, among others, platforms for food delivery (for example, Deliveroo), urban transport (Uber) and cleaning (Helpling), while the latter includes platforms for non-manual work such as design, computer-programming, accounting, transcriptions, translations, and data entry: examples are Upwork, Freelancer.com and Fiverr. The other main criterion distinguishes platforms that allocate jobs in full, as whole projects to individual professional freelancers (design of the logo of a company or translation of a complete document, for example through the platform Upwork) or small parts of it to myriad non-specialists (“micro-tasks” such as identification of objects in an image, or translation of only one or few sentences, as on Amazon Mechanical Turk).

Barely visible in the media and less concerned by legal fights so far, all-online platforms are nevertheless particularly interesting to study. With loose geographical boundaries, workers are exposed to wide competition that drives remunerations down and sometimes exposes them to unconventional working hours and possibly overtime – for example, to meet demand from clients in different time zones (Graham and Anwar, 2019). Thus, the conditions for embeddedness may be more difficult to meet. This is why Wood et al. (2019b) choose precisely this setting to undertake the first-ever study of embeddedness in the platform economy – with particular focus on global platforms for full freelancing projects. They find instances of embeddedness in the sense of Peck (2013)'s “soft Polanyi” (section 2) which is also similar to the view of Granovetter (1985): many of the workers they observe rely on their peer networks of, for example, friends, kin or even co-workers to get tasks done. To some extent, they restore the personal relationships that platforms' formal reputation systems obfuscate (subsection 5.3). However, workers appear disembedded in the “hard Polanyi” (Peck, 2013) sense that Granovetter allegedly left aside, and that sees embeddedness as absence of commodification: without labor regulations and rights, they are exposed to fluctuations in the labor market, and have limited access to healthcare and social protection.

It is tempting to try and generalize these ideas to other areas – notably micro-work, the other main sub-category within all-online platform labor. Here, one would also observe absence of labor rights and exclusion from welfare. In terms of peer networking, however, results from the literature are mixed. A team at Microsoft Research mapped the communication ties of Amazon Mechanical Turk workers and found that they constitute a structured network (Yin et al., 2016). In a related ethnographic study across four different platforms (Gray et al., 2016), they found that there is collaboration, sometimes spontaneously re-created by workers regardless of platforms' unsupportive policies. But before interpreting these results in terms of micro-workers' network embeddedness, two caveats are in order. First, in the network maps of Yin et al. (2016), only 13.4% of workers are connected, so that there
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is a long tail of disembeddedness as per Granovetter’s original definition. Second, the network is enabled by forums, a specificity of Amazon Mechanical Turk that may have no equivalent elsewhere. Initiatives to raise awareness and improve working conditions have coalesced around this platform, older and better-known than its competitors.

These studies place emphasis on the social networks of peers and focus exclusively on individuals (I-I, left panel of figure 2). They remain silent on the economic ties I-F that link individuals to firms (or platforms or other economic organizations that shape the production process), represented as gray lines in the central panel of figure 2. Neither do they make explicit any economic linkages between firms (or platforms, etc.), represented as black thick lines in the central panel of figure 2 (F-F). Without these economic dimensions, network analysis cannot link social ties such as mutual help and support to the economic positioning of individuals in the productive structure unfolding around the platform. It is necessary to simultaneously address the two, as schematically represented in the right panel of figure 2, which is also consistent with the multi-level structure of figure 1. To move forward in this direction, I now explore different platform business models and probe them against the above-outlined multi-level view of embeddedness.

<figure><img src="image_6.png" /><figcaption>**Fig. 2** Different dimensions of embeddedness. Nodes are actors (cyan circles = individuals, black squares = firms) and lines are ties between actors (black = inter-firm ties *F* − *F*, cyan = inter-individual ties *I* − *I*, gray = individual-firm ties *I* − *F*). Left: social (*I* − *I*) network. Center: economic (*I* − *F* and *F* − *F*) networks. Right: multilevel structure of social and economic networks. Source: author’s elaboration.</figcaption></figure>

# 4 An inventory of platforms

To provide empirical support for these ideas, I draw on a comprehensive study of platform labor in France, DiPLab (“Digital Platform Labor”), undertaken in 2017-19 (Casilli et al., 2019). France offers an original perspective relative to extant literature focused on the English-speaking world, while still enabling cross-national compa-
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rability and allowing generalizability of (many) findings beyond its borders. Its de-
demand for remotely-provided data services is high because it is investing heavily in
the development of digital technologies and in particular, of artificial intelligence.
Supply is sizable too, as the country features a mix of international platforms (that
operate mostly, if not exclusively, in English) and local ones (mostly in French),
offering a range of options to workers. While in principle, one may expect online
labor to be undertaken anywhere, competition is not always global because some
tasks require language proficiency or local knowledge. It is for this reason that even
if a lot of the online workforce is located in low-income countries in the Global
South (Casilli, 2017; Graham et al., 2017), niches remain in the richer North.

The dataset that I use here consists of a detailed inventory of online labor plat-
forms and mobile applications in use in the country, with information on their
company structures, business models, history, location, financial situation, market-
ing strategies and human resources. A total of 28 platforms have been identified,
combining information from different sources: business databases such as Crunch-
base and societe.com, a local repertoire; log data from NetBusinessRating, a ded-
icated discussion forum where workers share their reviews of platforms; and a set
of exploratory interviews that asked workers to name the platforms they used and
those they were at least aware of. Once compiled and double-checked for complete-
ness, this list was enriched with details for each of the platforms, taken from their
websites, press releases, media features, and in some cases personal communica-
tions with founders or managers. The majority of these platforms offer online-only
micro-working services, though some of them do so secondarily, their main activ-
ity concerning micro-tasks that requires physical presence in some place, like tak-
ing pictures of products in shops (subsection 3.2). Other platforms included in the
inventory offer inter-mediation of full-fledged freelancing services such as design
and computer programming. The broad scope of the inventory allows comparisons
across cases and types (notably micro-work and freelancing), and helps to distin-
guish widespread practices from any idiosyncrasies.

As a complement to this data, I use a set of 92 in-depth interviews with online
workers, clients, platform staff and other stakeholders, mostly though not exclu-
sively based in France. For the purposes of this paper, interviews are solely meant
to provide concrete examples of configurations that may seem otherwise abstract or
unfamiliar, and to support my interpretation of results.

5 Platform business models and embeddedness

Observation of the selected platforms clearly indicates that they adopt two main
types of business models. I now illustrate them by expanding from some first results
published in the DiPLab project report (Casilli et al., 2019). I then extend the dis-
cussion to the question of how these elements inform the analysis of embeddedness
framed above.
CV détaillé
5.1 Platform as markets: intermediaries

Some of the observed platforms function just as classical textbook cases of two-
sided market intermediaries (section 3). The prototypical example of this mode of
functioning is Amazon Mechanical Turk. The platform organizes interactions be-
tween two user groups, workers on the one side and clients (called “requesters”)
on the other, and provides the technical infrastructure upon which their activities
occur. This model mimics a lean, decentralized marketplace where the intermediary
is simply a facilitator, and decisions are left to clients (how much to pay for a task,
how many workers should complete it, how long it should be available on the site)
and workers (what tasks to do).

For the system to run as smoothly as possible, the platform offers multiple built-
in functionalities so that it can host the whole process internally, end-to-end (figure
3, top panel). Once logged in, workers can browse and choose from available tasks.
They then accept the conditions imposed for these tasks (if different from the general
terms of use of the platform), execute them, submit them and claim payment. On the
side of the client, the platform makes available a range of tools and templates to de-
sign tasks, post them on the site, review and accept (or reject) workers’ submissions,
and make payments at the end. On Mechanical Turk, all these functions are accessi-
ble through an API (Application Programming Interface) that obviates the need for
any other form of personal contact between clients and workers. The latter remain
anonymous and their personal characteristics are invisible to the former<fnref n="2" />. From the
viewpoint of the requesting client, the transaction is technically un-distinguishable
from any remote procedure call, completely de-personalizing the labor relationship.

After the successful launch of this market-oriented model by Amazon in the mid-
2000s, many other micro-tasking platforms such as the American Microworkers and
the French Foule Factory have adopted variants of it. Most freelancing platforms like
those observed by Wood et al. (2019b) function in about the same way, though with
some adaptation. Instead of letting workers get tasks on a first-come, first-served ba-
sis as on Mechanical Turk, freelancing platforms let clients select workers based on
their characteristics, track record and possibly interest in their request. This means
that there is no anonymity, and that contact between client and worker is not only
allowed but encouraged. Remunerations are not fixed by the client and equal for
all participating workers, but negotiated on a case-by-case basis, often based on a
quote provided by the worker (and sometimes, they are the outcome of competi-
tive bidding in an auction). Interestingly, my data show that pricing policies differ
markedly: freelancing platforms subsidize clients and charge commission fees to
workers, while micro-working platforms subsidize workers and charge only clients

<footnote n="2">² Specific functionalities allow clients to request that workers meet some pre-selected requirements (skills or socio-demographic characteristics), but it is the platform that operates the selection through automated worker screening and qualifications.</footnote>
## PAOLA TUBARO

LRI- CNRS
Bât. 660 Université Paris Sud
91405 Orsay Cedex

Email: paola.tubaro@lri.fr

Blog : http://databigandsmall.com/

Twitter : @ptubaro

## SITUATION ACTUELLE

Depuis jan. 2016, Chargée de recherche CNRS, section 36 (sociologie), affectée au Laboratoire de Recherche en Informatique (LRI, UMR 8623), Orsay.

## CARRIÈRE

2009-15, Université de Greenwich, Londres, GB :

* 2014-15, Reader (≈ équivalent MCF HDR hors classe, titulaire) en sociologie économique

- Faculté d'économie et gestion : Directrice de la formation doctorale, Membre du comité de pilotage de la recherche, Responsable du soutien aux jeunes chercheur.e.s.

- Faculté de sciences : Membre du conseil scientifique de l'école doctorale.

* 2011-14, Senior Lecturer (≈ équivalent MCF 1ère classe, titulaire).

* 2009-11, Lecturer (≈ équivalent MCF, titularisée en 2011).

2007-09, Centre Maurice Halbwachs (CMH, UMR 8097), Paris : Post-doctorante.

2003-06, Université de Cergy-Pontoise : Attachée Temporaire d'Enseignement et Recherche.

2001-03, Université de Cergy-Pontoise : Monitrice de l'enseignement supérieur.

2000-03, Académie de Versailles : Allocataire de Recherche.

1999-2000, Université de Padoue, IT : Boursière.

1998-99, Fondation L. Einaudi, Turin, IT : Chargée d'études.

## FORMATION - DIPLOMES

2000-04, Doctorat en Sciences Economiques. Co-tutelle, Université de Paris Nanterre et Université J.W. Goethe de Francfort-sur-le-Main, DE.

* Subvention de mobilité internationale du DAAD (agence allemande pour les échanges universitaires).

* Mention très honorable, félicitations du jury, proposition de subvention pour publication et prix de thèse.

* Lauréate du prix de thèse de STOREP, association savante italienne.

1999-2000, DEA d'Histoire de la Pensée Economique. Ecole Normale Supérieure de Fontenay/Saint-Cloud. Major du DEA, mention très bien.

1997, Master professionnel en Gestion des organismes à but non lucratif. New York University, US. Financé avec une bourse d'excellence de Fondation CARIPLO, Milan, IT.

1991-97, Licence et Master (cursus de 5 ans) en Sciences Economiques et Sociales. Université Bocconi, Milan, IT. 110/110 cum laude et subvention pour publication. Lauréate du prix de Fondation Stelline, Milan.
(Casilli et al., 2019)<fnref n="3" />. Despite these differences, most freelancing platforms can be said to function as market-like structures.

If digital platforms are often praised for their capacity to reduce transaction costs (section 5.3), marketplace-like structures for labor inter-mediation fail to achieve this. The time that workers spend searching for tasks, and working on tasks that are rejected or ultimately not submitted (often due to unclear instructions from requesters) is a cost that, on Amazon Mechanical Turk, results in a large gap between the $11 per hour that the average requester pays, and the median hourly wage of only $2 that workers earn (Hara et al., 2018). This is also true of most global online freelancing platforms, where workers spend considerable time searching for requests, applying, bidding unsuccessfully and waiting for work (Wood et al., 2019b). The massive over-supply that characterizes online labor platforms both in freelancing and micro-work (Graham and Anwar, 2019; Schmidt, 2019) also contributes to raising search costs for workers who need to set up alert notifications, connect several times a day, or keep their screens continuously on in order not to miss opportunities.

Clients also face high transaction costs – in the form of policing and enforcement costs. Clients struggle to monitor anonymous external contributors, and platforms’ reputation systems only provide signals of potential worker quality, without guaranteeing engagement or performance. Thus, requesters have set up multiple solutions to assure quality, some of them expensive: having several workers do the same task and choosing the majority solution, or posting follow-up tasks that ask workers to check the outputs of others (Vaughan, 2018). Clients’ demand for quality is increasing today, as data security becomes a major concern for large companies that use proprietary data-sets and that need to protect their cutting-edge R&D activities from the gaze of competitors. Thus, they become wary of generalist platforms where anyone can see the posted tasks and, worse, unidentified contributors can access the underlying data.

Another reason why high transaction costs may arise for clients is the growing demand, at least by the most technologically advanced among them, for specialist software infrastructures with state-of-the-art customized features. In particular, there are rising expectations regarding annotation and labeling tools such as those needed to prepare training data-sets for artificial intelligence algorithms (Schmidt, 2019; Tubaro and Casilli, 2019). Transaction cost theory (Williamson, 1981) suggests how provision of such specific assets is unlikely to occur on the open market, requiring instead tighter, long-term engagement between the involved parties. It is a major challenge to Amazon’s model.

<footnote n="3">³ According to two-sided market theory (Evans and Schmalensee, 2016), this means that freelancing workers are less price-sensitive than their clients, while the opposite is true of micro-workers. See section 3.</footnote>
# RECHERCHE

## Domaines

Sociologie économique ; Sociologie des organisations ; Sociologie des réseaux sociaux ; Socio-économie des plateformes numériques ; Données socio-économiques.

## Responsabilités collectives et d'animation de la recherche (actuelles)

Co-organisatrice de la XL Sunbelt, quarantième conférence annuelle de la INSNA (International Network for Social Network Analysis), Paris, 2-7 juin 2020 (environ 1 000 participants attendus).

Depuis sep. 2019, Membre du Comité de direction de la Revue Française de Sociologie.

Depuis juin 2019, Membre du Comité Local de l'Institut Pascal, Université Paris-Saclay.

Depuis oct. 2018, Membre du bureau de la Maison des Sciences de l'Homme (MSH) Paris-Saclay.

Depuis nov. 2017, Représentante (suppléante) du CNRS dans le Comité de Programmes de l'Institut de Convergence DataIA.

Depuis fèv. 2017, Co-fondatrice du réseau européen ENDL (European Network of Digital Labor studies).

Depuis juin 2016, Membre du comité de rédaction, Sociology.

Depuis mai 2014, Membre du comité de rédaction, Journal of Economic Methodology.

Depuis jan. 2013, Co-coordinatrice (avec A. D'Angelo, Université de Nottingham) du Social Network Analysis Group de British Sociological Association (BSA-SNAG).

Membre de: British Sociological Association (BSA), European Group for Organizational Studies (EGOS), International Network for Social Network Analysis (INSNA), American Economic Association (AEA).

## Responsabilités collectives et d'animation de la recherche (dix dernières années)

2019, Co-organisatrice, ateliers « International Network on Digital Labor », Toronto, CA, 3 oct. et Paris, FR, 14 juin.

2019, Co-organisatrice, journée grand public (250 participants) sur « Les plateformes de micro-travail : enjeu pour l'intelligence artificielle, enjeu pour l'emploi ? », France Stratégie, Paris, 13 juin.

2019, Membre du comité de recrutement pour un poste de professeur assistant (profil « Numérique et organisations »), Sciences Po Paris.

2019, Membre du comité scientifique, Junior Conference on Data Science and Engineering (JDSE2019), Université Paris-Saclay, 12-13 sep.

2019. Membre du comité scientifique, 4ème Conférence Européenne sur les Réseaux Sociaux (EUSN2019), ETH Zurich, CH, 9-12 sep.

2018, Co-organisatrice, table ronde sur « Le moment big data des sciences sociales: quel accès aux données du web et des médias sociaux ? » soutenue par la Revue française de sociologie, Sciences Po Paris, 6 déc.

2018, Co-organisatrice, « More than complex: large and rich network structures », Satellite de International Conference on Network Science (NetSci2018), Paris, 12 juin.

2018, Membre du comité de recrutement pour un poste de professeur assistant (profil « Inégalités, usages et effets du numérique »), Sciences Po Paris.

2018, Membre du comité scientifique, Junior Conference on Data Science and Engineering (JDSE2018), Université Paris-Saclay, 13-14 sep.

2017-19, Membre du comité de lecture, Revue française de sociologie.

2017, Organisatrice de l'atelier « Recent Ethical Challenges for Social Network Analysis » (RECSNA17), IEA de Paris, 5-6 déc.
## 5.2 Platforms as firms: multiple layers

To reduce transaction costs, an alternative model has recently emerged, in which the workforce is managed through vendor relationships on behalf of (mostly large) corporate customers. In this case, the organization of the workflow is managed like in a firm, which centralizes all transactions and does not need the price system to ensure coordination. Champions of this model are three large and well-known actors of the global digital data business, notably Appen, Lionbridge and Pactera. This does not mean that they employ workers for a salary as traditional companies do, as their costs would raise too much. Rather, they arrange tightly-knit outsourcing networks of providers and intermediaries coordinated through a set of contracts and common infrastructures. Centralized direction distinguishes them from platform-as-market models, while multiplicity of actors demarcates them from classical firms.

As a result, the whole work process is sliced into several “layers” with different interlocutors in each of them (figure 3, bottom panel). First, potential new workers see advertisements of online earning opportunities on standard jobbing websites, such as Monster.com. They apply and then go through a selection process, which may include an interview, and is managed by the vendor that posted the ads – for example Appen – or one of its subsidiaries. Selected workers are then invited to connect to a dedicated platform, or another external vendor, to establish a contract. In contrast to simple, market-like platforms where labor is systematically paid by piece-rate, here contracts often specify a regular amount of daily or weekly time that the worker commits to, for a generically defined type of tasks rather than a single, specific one (although the worker may at times be offered less work than agreed, or no work at all, depending on clients’ demand), and a hourly remuneration. Finally, contracted-out workers are directed to the platform that provides the technical infrastructure to execute tasks. This is often a closed, proprietary platform belonging to the final client, a monopsonist: for example UHRS (Universal Human Relevance System) for Microsoft, RaterHub for Google and TryRating for Apple. The functioning of these technical platforms is highly confidential, with no access allowed from the outside and often, not even a public web page. Its management is often entrusted to another sub-contractor, notably if there is bespoke technical infrastructure that requires maintenance, or if there is a need to supervise a pool of workers operating in the same premises. There is evidence that providers in India, Indonesia, the Philippines, and parts of Africa set up offices where they manage teams of local workers (Graham et al., 2017; Graham and Anwar, 2019; Roberts, 2019; Schmidt, 2019). Such arrangements are particularly interesting for large-sized client companies owing to the relatively low cost of labor and the high technical expertise in some of these countries (Murali, 2019). Evidence so far is that such arrangements are less common in Europe and North America, but can be observed in specific cases, for example, when data need to be accessed securely in a dedicated onsite facility.

One interview with a female micro-worker whom I will call J., illustrates concretely the multi-layer structure that the worker is integrated into, and its global outreach. A resident of South-Eastern France, J. was contracted by a Chinese data company to do transcriptions on behalf of an American client, the producer of a
2017, Co-organisatrice d'une session plénière sur « Visualisation and social networks in mixed-methods sociological research », Conférence annuelle de British Sociological Association, Manchester, GB, 6 avr.

2016-19, Co-organisatrice du Séminaire d'analyse des Structures et des Processus Sociaux (SPS), Maison de la Recherche, Paris (6-8 séances/an).

2016, Co-organisatrice de la 2ème Conférence Européenne sur les Réseaux Sociaux (EUSN 2016), Sciences Po Paris, 14-17 juin (250 participants).

2015-17, Membre du Comité de rédaction, Revue française de sociologie.

2014, Co-organisatrice d'un atelier sur « Mixed method approaches to social network analysis », Middlesex University, Londres, GB, 12 mai.

2013, Membre du comité de recrutement pour un poste de chargé de recherche, IRSTEA, Antony.

2010-12, Membre du bureau de UK Social Networks Association (UKSNA).

## Contrats et subventions obtenues

2019-22, Co-responsable scientifique (avec A.A. Casilli et U. Laitenberger, Telecom Paris), « The HUman Supply cHain behind smart technologies » (HUSH), financé par l'ANR (€ 348k).

2018-20, Responsable principale (avec A. Delfanti, Université de Toronto, CA, et A.A. Casilli, Telecom Paris), « International Network on Digital Labor – Kickoff Workshops » (INDM-KW), co-financé par CNRS et Université de Toronto (€ 10k).

2018-20, Co-responsable scientifique (avec O. Chagny, IRES, et A.A. Casilli, Telecom Paris), « Les nouveaux intermédiaires du travail B2B : comparer les modèles d'affaires dans l'économie numérique 'collaborative' », financé par la DARES (€ 100k).

2017-19, Co-responsable scientifique (avec A.A. Casilli, Telecom Paris), « Digital Platform Labor – DiPLab », co-financé par MSH Paris-Saclay (€ 24k) et France Stratégie (€ 12k).

2017-18, Co-responsable scientifique (avec A.A. Casilli, Telecom Paris), « Organizing Platform Labor - OPLa », financé par Force Ouvrière et IRES (€ 32k).

2017-18, Responsable principale (avec P. Caillou, Université Paris Sud, A.A. Casilli, Telecom Paris, et E. Penalva-Icher, Université Paris Dauphine), « REseaux et Simulations : usages Technologiques et Opinions multiples sur les plateformes numériques dans les marchés de la restauration » (RESTO), financé par la Mission pour l'Interdisciplinarité du CNRS (€ 19k).

2017, Responsable principale (avec A.A. Casilli, Telecom Paris), « Recent Ethical Challenges for Social Network Analysis », financé par MSH Paris-Saclay (€ 3,5k).

2017, Responsable, « La sociologie des réseaux sociaux en Chine », financé par Campus France (€ 2k).

2016, Co-responsable scientifique (avec A.A. Casilli, Telecom Paris), « Sharing Networks », financé par Télécom ParisTech, Fonds Action Carnot (€ 5k).

2014-17, Co-responsable scientifique (avec F. Pallotti, Université de Greenwich, et A. Lomi, Université de la Suisse Italienne), « Concurrence, collaboration et performance des organisations. Une approche par les réseaux », financé par l'Université de Greenwich (€ 80k).

2014-17, Co-responsable scientifique (avec M. Ugur, Université de Greenwich), « Gouvernance d'entreprise, structure de marché et innovation en présence d'effets de réseaux », financé par l'Université de Greenwich (€ 80k).

2012-13, Responsable, « ICCU – Internet Censorship and Civil Unrest », financé par l'Université de Greenwich (€ 5k).

2011-12, Responsable principale (avec A.A. Casilli, Telecom Paris), « Testing the Hypothesis of the End Of Privacy (THEOP) », financé par Fondation CIGREF, Paris (€ 30k).

2011, Co-responsable scientifique (avec C. Smith, Université de Greenwich), « Eating Disorders: new perspectives and a transdisciplinary approach », Université de Greenwich (€ 15k).
<figure><img src="image_7.png" /><figcaption>**Fig. 3** Two models of platform inter-mediation for micro-work. Top panel: intermediaries in market-like two-sided structures of interaction. Bottom panel: firm-like multi-layer structures. Cyan circles = workers, black squares = final clients, white large circle = marketplace platform, white rectangles = firm-like platforms, their contractors and subsidiaries. Source: author's elaboration.</figcaption></figure>

vocal assistant. J. had to listen to recordings of the interactions of French users with this vocal assistant, check them against the automated transcriptions that the assistant had done, and correct any errors. She was aware of micro-workers in neighboring countries who were doing the same tasks in their own languages, and they were all under the supervision of a subcontractor in Italy who managed day-to-day issues and practicalities. She received US tax forms for the income she earned.

Under these conditions, transaction costs go down. Workers do not have to spend time searching for tasks, because they receive assignments every day or every week, their only choice being whether to accept them or not. Because the system is tightly managed and deals with large orders, workers usually enjoy better remunerations and more predictable working hours than with market-like platforms. A., a 40-year-old mother of two who lives in Southern France, has been doing 20-30 hours a week of tasks on an American platform for the last 3 years. Throughout this period, she arranged never to take holidays in order not to miss assignments. Although she considers this activity temporary and plans to change job when her children grow up, she is relatively satisfied of her pay of 15 euros per hour – which is above the
2010-13, Co-responsable scientifique (avec C. Fischler, CNRS et A.A. Casilli, Telecom Paris), « La sociabilité 'Ana-mia': une approche des troubles alimentaires par les réseaux sociaux en ligne et hors ligne », financé par l'ANR (€ 300k).

## Autres participations à projets

2011-15, Responsable d'une tâche, « Data without Boundaries », financé par la Commission Européenne (7ème programme cadre, responsable scientifique : R. Silberman, CNRS).

2008-09, Coordinatrice d'un volet de « Council of European Social Science Data Archives », financé par la Commission Européenne (7ème programme cadre, responsable scientifique : K. Schürer, Université Essex).

2008, Réalisation d'une enquête dans le cadre du réseau d'excellence européen EQUALSOC (6ème programme cadre).

## Expertises

Evaluations de demandes de subventions de recherche pour : *Riksbankens Jubileumsfond*, SE (2019) ; ANR (2016, 2019) ; *Pontificia Universidad Católica del Perú*, PE (2019) ; Fonds Indépendant pour la Recherche, DK (2017, 2018) ; Centre National pour la Science (*Narodowe Centrum Nauki*), PL (2016) ; Fonds National Suisse pour la Recherche, CH (2013, 2015, 2016) ; *Economic and Social Research Council*, GB (2013) ; ANVUR, Agence italienne d'évaluation des Universités, IT (2012).

Evaluation de propositions d'ouvrages pour les maisons d'édition Cambridge University Press, Routledge, Sage, Wiley.

Evaluation de projets d'articles pour les revues *Social Networks*; *Socio-Economic Review*; *Sociology*; *British Journal of Sociology*; *Current Sociology*; *Sociological Research Online*; *Revue française de sociologie*; *Information Systems Research*; *Computational and Mathematical Organization Theory*; *Simulation Modelling Practice and Theory*; *Symmetry*; *Field Methods*; *Methodological Innovations Online*; *Qualitative Methodology*; *International Journal of Social Research Methodology*; *Communication Methods and Measures*; *Health*; *Health Promotion International*; *World Medical & Health Policy*; *International Studies in the Philosophy of Science*; *Journal of Economic Methodology*; *History of Political Economy*; *European Journal of the History of Economic Thought*; *Journal of the History of Economic Thought*; *History of Economic Ideas*; *Cahiers d'Economie Politique*; *Annales Histoire Sciences sociales*; *Revue d'Economie Régionale et Urbaine*; *International Journal of Management Practice*; *Journal of Archaeological Method and Theory*; *Procedia – Social and Behavioural Sciences*; *Communications*; *Terminal*.

## Séjours d'enseignement et recherche à l'étranger

2016-19, Professeure invitée et membre du conseil doctoral, Université de l'Insubria, Varese, IT (2 semaines/an).

2016-18, Professeure invitée, Université de Greenwich, Londres, GB (1 semaine/an).

2016, Chercheuse invitée, programme « Vers une société du numérique », Institut Français & Consulat Général de France au Québec, CA (2 semaines).

2015, Formatrice externe invitée, Université de Lund, SE (1 semaine).

2015, Professeure invitée, Université de Toulouse Jean Jaurès (1 mois).

2014, Formatrice externe invitée, Université de Tel Aviv, IL (1 semaine).

2012, Enseignante invitée, ABRS, Hong Kong, HK (1 semaine).

2011, Terrains de recherche collaborative « Réseaux organisationnels en microfinance », Chennai, IN and Dar-es-Salaam, TZ (2 semaines).

2009, Chercheuse en résidence, Duke University, US (3 semaines).

2008, Séjour de recherche collaborative, Fondation Suisse pour la Recherche en Sciences Sociales (FORS), Université de Lausanne, CH (1 mois).

2004, Chercheuse en résidence, Institut Max Planck pour les Systèmes Complexes, Dresde, DE (1 mois).
French minimum wage. She also signed up with a marketplace platform but does not find it interesting, and uses it rarely.

On their side, clients are reassured about quality and therefore, incur lower polic-
ing and enforcing costs. These platforms that Schmidt (2019) qualifies as “second
generation” in comparison to earlier market-like models à la Amazon Mechanical
Turk, know their workers and are able to set up schemes to assure quality like firms
do: careful selection of who does what tasks, attribution of monitoring responsibili-
ties to the most motivated workers, creation of qualified teams to do more complex
tasks together. Further, these structures offer greater confidentiality and security in
that clients’ data and technical tools (for example, specialist annotation and labeling
software used to prepare training data-sets for artificial intelligence algorithms) are
only accessed by selected workers and are under the direct control of the client or
one of its suppliers, as on UHRS.

5.3 Platform-market, platform-firm and embeddedness

How do the preceding remarks relate to the concept of multi-level embeddedness outlined in section 2? Recall that the idea is to reconstitute the inter-individual *I* − *I* and the inter-firm *F* − *F* networks of ties, and the affiliation network that links in-dividuals to firms *I* − *F*. Let us temporarily leave aside the inter-individual network *I* − *I* on which the literature has already provided evidence as discussed in subsec-tion 3.2. The above discussion of business models can help reconstitute the other two which, as mentioned, consist of economic relationships.

In the platform-as-market model, there is no F-F network of ties between firms. Clients act independently and autonomously of one another, and their only inter- locutor is the platform. If there is a network, it is star-shaped, with the platform at the center. Similarly, affiliation ties I-F are evanescent. Workers are not em- ployees and their engagement with the platform (and/or its clients), construed as a spot contract between independent businesses, deprives them of the human contact and sense-making that normally accompany work. Excess supply of labor (Graham and Anwar, 2019) makes them easily replaceable, and in the case of micro-work, they are anonymous in the eyes of their clients as mentioned above. Further, inter- views suggest that micro-workers do not always know the identity of the client or the purposes of the tasks (even though platforms encourage requesters to disclose this information). For example, D. described a videogame-like task in which she had to move characters back or forth on her screen depending on their appearance (North African or French). She ignored who was sponsoring this task and what its purposes were: developing a tool to monitor prejudice or to spread anti-immigrant ideas? Under these conditions, decisions at the client (F) level affect conditions at the worker (I) level, but there can be no inter-level feedback. In sum, the platform- as-market model comes with disembeddedness in a multi-level sense – whether or not workers are embedded in the narrower sense of having a network of peers I-I who may support their activity.
# PUBLICATIONS

## Ouvrages

Kalainathan D., Goudet O., Caillou P., Sebag M., Tubaro P., Bourdu E., Weil T. (2017). *Portraits de travailleurs : Comprendre la qualité de vie au travail*. Paris, Presses des Mines.

Casilli A.A., Tubaro P. (2016). *Le phénomène « pro-ana ». Troubles alimentaires et réseaux sociaux*. Paris, Presses Universitaires des Mines.

Tubaro P., Casilli A.A., Sarabi Y. (2014). *Against the hypothesis of the “end of privacy”: An agent-based modelling approach to social media*. Springer, SpringerBriefs in Digital spaces.

Tubaro P. (1999). *Critica della ragion nonprofit*. Rome: DeriveApprodi.

## Direction de numéros spéciaux de revues

Tubaro P., Ryan L., Casilli A.A., D'Angelo A. (en préparation). Direction d'un numéro spécial de la revue *Social Networks* sur « Recent ethical challenges in social network analysis ».

Bastin G., Tubaro P. (2018). Direction d'un numéro spécial de la *Revue française de sociologie* (n. 59/3) sur « Big data, société et sciences sociales ».

D'Angelo A., Ryan L., Tubaro P. (2016). Direction d'un numéro spécial de la revue *Sociological Research Online* (n. 21/2) sur « Visualization in mixed-methods research on social networks ».

Tubaro P., Angner E. (2008). Direction d'une section spéciale de la revue *Journal of the History of Economic Thought* (n. 30/1) sur « The future of history of economics: Young scholars' perspective ».

## Articles dans des revues à comité de lecture

Tubaro P., Casilli A.A. (2019). Micro-work, artificial intelligence and the automotive industry. *Journal of Industrial and Business Economics*, 46 (3): 333-345.

Bastin G., Tubaro P. (2018). Le moment big data des sciences sociales. *Revue française de sociologie*, 59 (3): 375-394.

Pallotti F., Tubaro P., Casilli A.A. & Valente T.W. (2018). "You see yourself like in a mirror": The effects of internet-mediated personal networks on body image and eating disorders, *Health Communication*, 33(9): 1166-1176.

Tubaro P. (2017). Les tensions entre sociologie et politique à l'aune d'une tentative de législation des sites web sur les troubles alimentaires, *SociologieS*, en ligne, URL : http://journals.openedition.org/sociologies/6387

Tubaro P., Ryan L., D'Angelo A. (2016). The visual sociogram in qualitative and mixed-methods research. *Sociological Research Online*, 21 (2), 1 <http://www.socresonline.org.GB/21/2/1.html>

Pallotti F., Tubaro P. & Lomi A. (2015). How far do network effects spill over? Evidence from an empirical study of performance differentials in interorganizational networks. *European Management Review*, 12 (3): 189-208.

Casilli A.A., Rouchier J., Tubaro P. (2014). How to build consensus in a health-oriented online community: modeling a 'pro-ana' forum. *Revue Française de Sociologie*, 55 (4): 731-763.

Rouchier J., Tubaro P., Emery C. (2014). Opinion transmission in organizations: An agent-based modeling approach, *Computational and Mathematical Organization Theory*, 20(3): 252-277.

Tubaro P., Casilli A.A., Mounier L. (2014). Eliciting personal network data in web surveys through participant-generated sociograms. *Field Methods*, 26 (2): 107-125.

Tubaro P., Mounier L. (2014). Sociability and support in online eating disorder communities: Evidence from personal networks. *Network Science*, 2(1): 1-25.

Tubaro P. (2014). A tale of two destinies: Georgescu-Roegen on Gossen. *History of Political Economy*. 46(1): 33-54.
Instead, the platform-as-firm model generates dense economic networks. The inter-firm *F-F* network consists of the contractual agreements between the final client (for example, Microsoft and its proprietary service UHRS), its vendors (for example, Pactera), their subcontractors (in charge of, say, managing the workforce on a daily basis or of maintaining the technical infrastructure) and any additional service provider (such as a jobbing website). The affiliation network *I-F* still includes no proper employment relationships, but it ties workers to those in charge of the direction of their activity: to the company or platform which contracted them out, to the final client who (hopefully) files tax documents for them, to the subcontractors who provide technical tools or day-to-day management. The client can know who the workers are and *vice-versa*, particularly when orders are large or repeated.

There is certainly here a form of embeddedness, reminiscent of the multi-level conception described by Brailly et al. (2016), whereby individuals are integrated into complex contractual structures that directly or indirectly orient their productive activity. Its specificity is the multi-layer configuration that distinguishes its outer appearance from more classical cases with just firms and individuals. This form may be dubbed “deep” embeddedness, following an intuition of Casilli et al. (2019) who talk about “deep labor” platforms to highlight the apparent similarity between their multiple-layer structure and the complex neural networks that constitute the building blocks of the mathematical field of *deep learning*, where “layers” are containers that receive input, transform it with sophisticated non-linear functions and then pass the results to the next layer. Beyond the surface, the reference to deep learning is motivated by the prominent place of the latter in the development of today’s artificial intelligence research, and its intensive use of online labor, particularly micro-work, for its needs.

But there’s more to the “deep” adjective in the case of the multi-layer structures described above. Depth signals opaqueness of the overall construction to the outside viewer, especially if it is part of a corporate net that stretches globally. The worker sees some of the layers (and typically, can name clients as discussed in subsection 5.2) but not necessarily the whole structure, and essential parts of it remain black boxes. For example, A. said she had no idea how the platform chose tasks for her to do. The reason why she never refused a task – at the expense of being exposed to disturbing material when she had to moderate violent or pornographic content – is that she feared a refusal might lead the platform to give her less work, but she had no way to check whether her apprehension was genuine.

Additionally, the “deep” metaphor points to the hidden role of labor, whose contribution to datafied production processes is essential but often left in the shadow (Gray and Suri, 2019). Corporate communication highlights the role of technology, not human contribution, especially in the artificial intelligence industry (Casilli, 2019; Casilli et al., 2019; Schmidt, 2019; Tubaro and Casilli, 2019). In this sense, laborers are deeply embedded in these multi-layer structures because their contribution is elicited in ways that are little visible from the outside – neither the final client such as UHRS, nor its main vendor such as Appen, hire them as salaried employees – but still integrate them in the system and to some extent, control their activities.
Casilli, A.A., Pailler F., Tubaro P. (2013). Online networks of eating-disorder websites: why censoring pro-ana might be a bad idea. *Perspectives on Public Health*, 133 (2): 94-95.

Casilli A.A., Tubaro P. (2012). Social media censorship in times of political unrest: A social simulation experiment on the UK riots. *Bulletin de Méthodologie Sociologique*, 115: 5-20.

Casilli A.A., Tubaro P., Araya P. (2012). Ten years of Ana. Lessons from a transdisciplinary body of literature on online pro-eating disorder websites. *Information pour les Sciences Sociales*, 51(1): 121-139.

Lazega E., Mounier L., Snijders T.A.B., Tubaro P. (2012). Norms, status and the dynamics of advice networks: A case study. *Social Networks*, 34 (3): 323-332.

Tubaro P., Cros M., Silberman R. (2012). Access to official data and researcher accreditation in Europe: Existing barriers and a way forward. *IASSIST Quarterly*, http://www.iassistdata.org/downloads/iqvol36_1_cros.pdf

Marr A., Tubaro P. (2011). Crisis in Indian microfinance and a way forward: Governance reforms and the Tamil Nadu model. *Journal of International Development*, 23(7): 996-1003.

Marr A., Tubaro P. (2011). Wholesale funding to microfinance and social development goals in Peru, Tamil Nadu and Tanzania. *Enterprise Development and Microfinance*, 22(4): 304-321.

Moscati I., Tubaro P. (2011). Becker random behaviour and the as-if defense of rational choice theory in demand analysis. *Journal of Economic Methodology*, 18 (2): 107-128.

Tubaro P., Casilli A.A. (2010). “An ethnographic seduction”: how qualitative research and agent-based models can benefit each other. *Bulletin de Méthodologie Sociologique*, 106 (1): 59-74.

Tubaro P. (2009). Is individual rationality essential to market price formation? The contribution of Zero-Intelligence agent trading models. *Journal of Economic Methodology*, 16 (1): 1-19.

Lazega E., Mounier L., Snijders T.A.B., Tubaro P. (2008). Réseaux et controverses: du pur effet des normes sur la dynamique des structures et les processus sociaux, *Revue Française de Sociologie*. 49 (3): 467-498.

Casilli A.A., Sanchez S., Tubaro P., Antille N. (2008). Négocier le plaisir dans la consommation alimentaire: une étude sur trois groupes de familles de migrants de l’aire métropolitaine de Los Angeles. *Cahiers de l’OCHA (Observatoire Cniel des Habitudes Alimentaires)*, 13: 108-116.

Tubaro P. (2008). Producer choice and technical unemployment: John E. Tozer’s mathematical model (1838). *European Journal of the History of Economic Thought*, 15 (3): 433-454.

Tubaro P., Angner E. (2008). The future of history of economics: Young scholars’ perspective. *Journal of the History of Economic Thought*, 30 (1): 81-84.

Tubaro P. (2006). Mathématiques et économie dans la détermination du 'salaire naturel' de J.H. von Thünen. *Cahiers d'économie politique*, 50: 59-85.

Tubaro P. (2005). Hermann, Rau, Mangoldt : les origines de la fonction d’offre de marché en Allemagne (1830-1870). *Recherches Economiques de Louvain*, 71 (2): 223-243.

Tubaro P. (2002). A case study in early mathematical economics: Pietro Verri and Paolo Frisi, 1772. *Journal of the History of Economic Thought*, 24 (2): 195-214.

Tubaro P. (2000). Un'esperienza peculiare del Settecento lombardo: la ‘scuola milanese’ di economia matematica. *Studi settecenteschi*, 20: 193-230.

### Articles dans actes de conférences avec comité de lecture

Tubaro P. (2018). Emergent relational structures at a “sharing economy” festival. *Proceedings of the 7th International Conference on Complex Networks and Their Applications*, L.M. Aiello, C. Cherifi, H. Cherifi, R. Lambiotte, P. Lió, L.M. Rocha (eds.), Dec 2018, Cambridge, UK, pp. 559-571.

Rouchier J., Tubaro P. (2011). Can opinion be stable in an open network with hierarchy? An agent-based model of the Commercial Court of Paris. *Procedia –Social and Behavioral Sciences*, 10: 123-131.
Both workers and their client(s) can be said to be deeply embedded. The client renounces the user-friendly interfaces of market platforms such as Mechanical Turk, and their offer of standardized technical tools, to develop its own infrastructure – generally lacking fancy communication solutions and sometimes even devoid of support services, as these are delegated to vendors and their subcontractors. The ties that bind a client to these vendors usually involve some mutual dependency due to asset specificity, that is, investment of the vendor in the development of tools and services that respond very precisely to the client’s needs, but would be difficult to re-deploy elsewhere in case of contract termination (Williamson, 1975, 1981).

Let us now re-introduce the question of the *I—I* social networks among individual workers, previously left aside. Such networks may exist under deep embeddedness. Some platforms invest in the creation of networking tools for their workers via online forums and chats, in the hope of increasing their engagement (Schmidt, 2019, p. 37). However in another sense, the siloed architecture of these platforms restricts interactions among workers: an example is UHRS, where different vendors manage the workforce and the few existing discussion boards are internal to each of them and therefore asynchronous (Gray et al., 2016). In practice, in such cases inter-individual ties *I—I* exist (almost) only between workers who share affiliation ties *I*—*F* to the same firm *F*ᵢ. Additionally, participation in these networks does not necessarily concern all workers: A. claims not to be in touch with anyone except (occasionally) platform support services, and not to know any other micro-worker.

Is deep embeddedness good or bad for workers? In exchange for lower search costs, it removes some of the flexibility and autonomy that disembedded, market-like platforms such as Mechanical Turk allow. Indeed workers have to accept a certain discipline (the amount of work they engage themselves to do regularly) and in some cases, supervision by others (whenever a subcontractor is in charge of workforce management). Discipline has some advantages: Gray et al. (2016) suggest that the internal organizational structures of each single vendor or subcontractor may enable mentoring and skill-building in ways that would not be possible on Mechanical Turk.

But there is a profound power asymmetry insofar as the client side retains the flexibility that workers lose – notably in terms of the possibility to dispose of the workforce if and when needed. An interview illustrates what this means. F. is a 25-year-old man from Northern France who used to work for an international deeply-embedded platform structure when he was a student. He had engaged himself to do one hour a day for seven days a week, and in this way, he earned about 400 euros a month – a welcome supplement to his meager student budget. Yet the platform discontinued his contract after six months, without any explanations.

Brailly et al. (2016) and Lazega (2016) show that in a multi-level structure, different levels have different temporalities, and require actors to adjust. Here, platforms move faster, and this a-synchrony comes to workers’ disadvantage.
## Autres articles

Tubaro P. (2018). La vie privée, un bien commun ? *Regards croisés sur l'économie*, 23(2) : 129-137.

## Contributions à ouvrages

Lazega E., Mounier L., Snijders T.A.B., Tubaro P. (à paraître). Dynamics of advice-seeking networks among judges at the Commercial Court of Paris. In *Social Network Dynamics by Examples*. T.A.B. Snijders et C.E.G. Steglich (éds.), Cambridge University Press.

Caillou P., Kalainathan D., Goudet O., Guyon I., Sebag M., Tubaro P., Bazet J.L., Bounfour A. (2019). Qualité de vie au travail et santé économique des entreprises : étude des causalités. In *Le travail en mouvement*, É. Bourdu, M. Lallement, P. Veltz, T. Weil (éds.), Presses des Mines.

Tubaro P., Casilli A.A. (2017). Enjeux sociaux des big data. In *Big data à découvert*. M. Bouzeghoub et R. Mossery (éds.) CNRS Editions, pp. 290-291.

Tubaro P. (2016). Formalisation and mathematical modelling. In *Handbook on the History of Economic Analysis*. G. Faccarello et H. Kurz (éds.). Aldershot: Edward Elgar. Vol. III, pp. 208-221.

Tubaro P. (2015). Microeconomics, History of. In: J.D. Wright (éd.), *International Encyclopedia of the Social & Behavioral Sciences*, 2nd edition, Vol. 15. Oxford: Elsevier, pp. 331-337.

Tubaro P. (2015). Tozer, John Edward on Ricardo. In: H. Kurz et N. Salvadori (éds.), *The Elgar Companion to David Ricardo*, Aldershot: Edward Elgar, pp. 566-572.

Lazega E., Mounier L., Tubaro P. (2011). Norms, advice networks and joint economic governance: The case of conflicts among shareholders at the Commercial Court of Paris. In *Does Economic Governance Matter? Governance Institutions and Outcomes*, D. Sunderland et M. Ugur (éds.). Aldershot: Edward Elgar, pp. 46-70.

Tubaro P. (2011). Computational Economics. In *The Elgar Companion to Recent Economic Methodology*. J. B. Davis et D. W. Hands (éds.). Aldershot: Edward Elgar, pp. 209-227.

Lazega E., Mounier L., Tubaro P. (2010). Dynamique des réseaux sociaux et apprentissage collectif: le cas du Tribunal de Commerce de Paris. In *Systèmes Complexes et Sciences Sociales*. H. Zwirn et G. Weisbuch (éds.). Paris: Vuibert, pp. 103-125.

Tubaro P. (2010). History of Economic Thought. In *21st Century Economics: A Reference Handbook*. R.C. Free (éd.). Sage, vol. I, pp. 3-11.

Tubaro P. (2009). Les mathématiques du plaisir et de la peine : la théorie du choix individuel de Hermann H. Gossen. In *La pensée économique allemande*. A. Alcouffe et C. Diebolt (éds.). Paris: Economica. 245-267.

Tubaro P., Lazega E., Mounier L. (2008). Further Explorations of the Spinning Top Model for Advice Networks and Collective Learning. In *Management et Réseaux Sociaux : ressource pour l'action ou outil de gestion*? M. Lecoutre et P. Lièvre (éds.). London: Hermès-Lavoisier. 202-212.

Tubaro P. (2001). Terzo settore. In *Lessico postfordista*. U. Fadini, A. Zanini (éds.). Milan: Feltrinelli. 313-316.

Tubaro P. (2001). Volontariato. In *Lessico postfordista*. U. Fadini, A. Zanini (éds.). Milan: Feltrinelli. 325-328.

## Comptes rendus d'ouvrages

Tubaro P. (2014). Linking micro, meso and macro. Compte rendu de G. Manzo (éd.) Analytical Sociology : Actions and Networks, Wiley, 2014. *Archives européennes de sociologie*, 55(3) : 495-503.

Tubaro P. (2014). Sociology and social networks (Compte rendu comparatif de trois livres). *Sociology*. 48(2): 410-16.

Tubaro P. (2011). Compte rendu de T. Stenger et A. Coutant, Ces réseaux numériques dits sociaux, numéro spécial de Hermès, n. 59, 2011. *Sociologie*, 2(4): 453-457.
# 6 Conclusions

I have shown that the early platform-as-market model embodied in Amazon Mechanical Turk *disembeds* workers, exposing them to high costs of participation to the platform (transaction costs) and, one might add, potential psycho-social risks due to lack of purpose and difficulty to give meaning to their work (for example when clients disclose too little information). The emerging multi-layer model adopted by, among others, Pactera and Appen *deeply embeds* workers, paying them more but also reducing their flexibility and subjecting them to stricter discipline and sometimes outright control, while also restricting their opportunities for peer interactions at least in some cases. With minor tweaks, the same can be said of clients. Market-like platforms offer them user-friendly interfaces and a range of off-the-shelf technical tools, but impose high enforcement costs and discourage development of specific assets: their contracts can be seen as arm's length ties in the sense of Uzzi (1997), therefore disembedded. Multi-layer platforms enable customization of technical tools and more controlled management of the workforce, but require engagement in tighter, longer-term contracts that are more difficult to terminate or change: they are more similar, in this respect, to Uzzi's embedded ties.

Epistemologically, the study undertaken showcases the benefits of blending traditions and disciplines. Transaction costs economics has helped to identify the two main business models of online labor platforms and the circumstances under which either of them is chosen, sometimes beyond the predictions of two-sided market theory. Social network analysis combined with economic sociology has provided the multi-level structure as a framework to analyze these business models and derive implications from them. Organization theory broadly interpreted links these different insights, interpreting platforms as coordination devices and raising the question of the modes and costs through which they function.

Implications for the sociological study of digital platforms are of import. To begin with, these results add an extra dimension to extant categorizations of labor platforms, summarized in subsection 3.2. Most freelancing and some micro-work platforms adopt the marketplace model, though they implement it differently, notably in terms of their pricing structures; while only some micro-work platforms embrace the multi-layer model as of yet. Remunerations and working conditions differ markedly. Specifically, deep embeddedness limits some of the worst consequences of the platformization of labor: it re-introduces some degree of information and sense-making for the worker, a certain regularity of engagement, and at least minimal structures of support. Therefore, a revised typology that also introduces a dividing line based on platforms' business model, in addition to the degree of qualification or the duration of the tasks they offer, will more accurately describe the diverse situations that workers face.

Further, this research exposes the limitations of the platform-as-market model, as industry leaders increasingly adopt the alternative multi-layer structures. It is too early to discern the effects of this ongoing evolution, but provisional hypotheses can be formulated. One is that asymmetries across clients may drive the future unfolding of these tendencies. The multi-layer model may become more prominent if it is
Tubaro P. (2008). Compte rendu de T. Raffaelli, G. Becattini, M. Dardi (éds.) *The Elgar Companion To Alfred Marshall*, Edward Elgar, 2006. *Marshall Studies Bulletin*. Vol. X.

## Logiciels

2013, THEOP ‘Testing the Hypothesis of the End-Of-Privacy’ (avec A.A. Casilli & Y. Sarabi)

2013, ANAMIA_F “Ana-Mia Forums” (avec A.A. Casilli & J. Rouchier).

2013, ANAMIA Egocenter (avec A.A. Casilli, L. Mounier, P. Maigron, P. A. Chardel, E. Masson, C. Fraïssé, J. Rouchier, C. Fischler).

## Articles de vulgarisation

Tubaro P., Kalainathan D., Sebag M., Caillou P. (2018). Ce qui rend les salariés heureux au travail. *The Conversation*, https://theconversation.com/ce-qui-rend-les-salaries-heureux-au-travail-89390

Casilli A.A., Tubaro P. (2017). Rethinking ethics in social network research. *The Conversation*, https://theconversation.com/rethinking-ethics-in-social-network-research-88988

Casilli A.A., Tubaro P. (2016). Le phénomène « pro-ana ». Par-delà le mythe de l’apologie de la maigreur sur Internet. *The Conversation*, https://theconversation.com/le-phenomene-pro-ana-par-dela-le-mythe-de-lapologie-de-la-maigreur-sur-internet-66344

Casilli A.A., Tubaro P. (2014). An open letter to the Italian Parliament, against the criminalization of “pro-ana” websites. *Medium*, http://www.anamia.fr/en/an-open-letter-to-the-italian-parliament-against-the-criminalization-of-pro-ana-websites/

Tubaro P. (2014). “Pro” ana? Sociability and support in eating disorder online communities. *Discover Society*, https://discoversociety.org/2014/11/04/pro-ana-sociability-and-support-in-eating-disorder-online-communities/

Tubaro P. (2014). Why online privacy is not dead: Negotiation and conflict in social media. *Discover Society*, https://discoversociety.org/2014/02/15/why-online-privacy-is-not-dead-negotiation-and-conflict-in-social-media/

## Tribunes dans la presse

Casilli A.A., Tubaro P. (2019). Travailleuse du clic, la double invisibilité. *L'humanité*, 2 mai.

Casilli A.A., Tubaro P. (2018). Notre vie privée, un concept négociable. *Le monde*, 24 janvier.

Casilli A.A., Tubaro P. (2017). Réprimer les sites pro-anorexie, une fausse bonne idée. *Libération et Le journal du CNRS*, 2 février.

Casilli A.A., Chardel P.A., Mounier L., Pailler F., Tubaro P. (2015). Un amendement qui met en danger les malades. *Libération*, 2 avril.

Sahuc N., Tubaro P. (2015). Criminaliser les sites pro-anorexiques revient à lutter contre les malades, pas contre la maladie. *Slate*, 2 avril.

Casilli A.A., Pailler F., Tubaro P. (2012). Pourquoi la censure et le filtrage ne marchent pas ? L’exemple des réseaux liés aux troubles de l’alimentation. *Le monde – Internet Actu*, 16 nov.

## Rapports

Casilli, A., Tubaro, P., Le Ludec, C., Coville, M., Besenval, M., Mouhtare, T., Wahal, E. (2019). Le micro-travail en France. Derrière l'automatisation, de nouvelles précarités au travail ? Rapport final du projet *Digital Platform Labor* (DiPLab).

Wearn P., Alvheim A., Buerli S., Isnard M., Kappi C., Kleiner B., Pedersen T., Schiller D., Shearman N., Silberman R., Smrekar T., Tubaro P., Welpton R. (2015). Convergence in accreditation, legal framework, and information security. Rapport pour le projet européen *Data without Boundaries*.
the preferred choice of larger or more powerful clients, but if smaller players cannot
afford the asset-specific investments it requires, they will have to be content with in-
creasingly less attractive market-like platforms, resulting in inequalities in access to
labor-powered data resources. The other is that, against a popular idea, the platform
economy may not mean the end of centralization – and possibly of more traditional
models of labor supervision. This insight goes against a defense line often adopted
by platforms in court cases that opposed them to workers. If they are mere interme-
diaries between independent businesses, as they typically claim, they have hardly
any responsibilities toward their workers, but if they are firm-like entities, they do.
The policy implications of the platform-as-firm model may strengthen a view of
the platform as an employer, thereby touching upon current lively disputes around
the legal status of platform workers (De Stefano, 2016; Prassl and Risak, 2016).

Related to the above, existing conceptualizations of platforms reveal their lim-
itations. Two-sided market economics (section 3), fits well with the platform-as-
market model, but less so with the multi-layer model. An organizational lens along
the lines of Gawer (2014) is more comprehensive, interpreting organization broadly
as a generic coordination device that may take different forms, each entailing
specific costs and incentives. However, Gawer's definition of platforms as meta-
organizations, which presupposes that members are "legally autonomous and not
linked through employment relationships" (p. 1240), sweeps under the carpet the
controversies surrounding the status of platform workers. A more suitable organiza-
tional perspective would stress how all online labor platforms are systems of coor-
dinating activities in view of supporting outsourcing. Both the market-like and the
multi-layer models aim to remove the need for employment relationships, allowing
the client to access labor on demand: they only differ in the way they achieve this,
one through a spot market system and the other through a set of (longer-term) sub-
contracting ties to other organizations. Both operate on a planetary scale and serve
a flourishing just-in-time economy, in contrast to the local labor market settings
of most embeddedness research – including the work of Polanyi and Granovetter
themselves. These new geographies of online labor (Graham et al., 2019) matter be-
cause they shift the balance of power in favor of capital (clients, platforms, and their
subsidiaries and contractors) and against labor – insofar as capital benefits from its
greater mobility compared to labor (Graham and Anwar, 2019). Online labor thus
appears as a site of power struggles – much like the large corporation of the twenti-
eth century – rather than a place where trade occurs between equals.

More generally, the findings illustrated in this article advance research on em-
beddedness within economic sociology. Critics asserted that focus on just the social
network of friends and kin is too narrow to really reconcile the social and economic
dimensions (section 2). I have submitted that the multi-level network analysis ap-
proach of Brailly et al. (2016) offers a solution by combining the social networks
of individuals *I* − *I*, the economic networks of firms *F* − *F*, and the (likewise eco-
nomic) affiliation network between individuals and firms *I* − *F*. Application of these
schemes to platforms suggests that economic networks may be even more important
than social networks as they reveal important asymmetries of power that affect ac-
tion. In the multi-level networks that represent market-like platforms, there are no
Wearn P., Buerli S., Isnard M., Kappi C., Kleiner B., Silberman R., Tubaro P. (2015). Researcher accreditation - current practice, essential features, and a future standard. Rapport pour le projet européen *Data without Boundaries*.

Casilli A.A., Mounier L., Pailler F., Tubaro P. (2013) Les jeunes et le web des troubles alimentaires : dépasser la notion de 'pro-ana'. Rapport final du projet ANR ANAMIA.

Tubaro P., Silberman R., Cros M., Cornilleau A., Kvalheim V., Kiberg D., Farago P. (2009). Access mechanisms and official statistics in the European Research Area. Rapport pour *Council of European Social Science Data Archives – Commission Européenne*.

## COMMUNICATIONS ORALES

### Présentations à colloques, séminaires et conférences scientifiques (sélection 2015-19)

2019, *Into the data workhouse: digital platforms, invisible labor, and automation*. Conférence du European Group for Organizational Studies (EGOS), Edinburgh, GB, 5 juil.

2019, *Digital platforms between organizations, markets and networks*. XXXIX Sunbelt, Conférence de INSNA (*International Network for Social Network Analysis*), Montréal, CA, 20 juin.

2019, *Networks of attention: Participation, knowledge-gathering and status at a business event*. XXXIX Sunbelt, Conférence de INSNA (*International Network for Social Network Analysis*), Montréal, CA, 20 juin.

2019, *Seeing the forest for the trees: Digital platform labor behind automation*. *S&O Research Day*, HEC Paris, 23 mai.

2019, *Dans la fabrique des algorithmes : plateformes, micro-travail et dynamiques d'externalisation*. Séminaire, INSEE, Montrouge, 14 mai.

2019, *Humans in the loop: Micro-workers behind artificial intelligence*. Conférence « *AI, Robotics and Work* » HEC Paris, 12 mar.

2019, *Que font les big data aux sciences sociales ? Retour sur une ‘crise’ annoncée*. Séminaire « Etudier les cultures du numérique », EHESS, Paris, 21 fév.

2019, *The human labour that makes AI possible: An empirical study of micro-work in France*. Présentation invitée, conférence « Automating the crowd », Alan Turing Institute, Londres, GB, 22 jan.

2018, *Microworking in France: an inquiry into the human labour that makes AI possible* (avec A.A. Casilli). Séminaire, OCDE : Direction de l'Emploi, du travail et des affaires sociales, Paris, 5 déc.

2018, *Dans les coulisses de l'IA: micro-travail, délocalisations et données personnelles, journée « Plateforme(s) : Utopies, Réformes ou Révolution ? »*, Université Sorbonne Nouvelle, Paris, 26 nov.

2018, *Micro-work, datafied economies, and AI: the French case* (avec A.A. Casilli). Conférence *Reshaping Work in the Platform Economy*, Amsterdam, NL, 26 oct.

2018, *Un champ de mines ? Éthique, droit et politique dans la recherche sur les réseaux sociaux. Présentation invitée à la conférence MARAMI (Modèles et analyse des réseaux : Approches Mathématiques & Informatiques)*, Avignon, 17 oct.

2018, *Click-work in the kitchen: How digital platforms transform labor in the restaurant industry*. Conférence *Work, Employment and Society* de British Sociological Association, Belfast, GB, 15 sept.

2018, *Old friends, new acquaintances and future partners: purposive networking in the “sharing” economy*. XXXVI Conférence INSNA Sunbelt, Utrecht, NL, 30 juin.

2018, *Organiser les micro-travailleurs ? Le cas de la France (avec M. Coville). Conférence « Travail et emploi à l'ère du capitalisme de plateforme »*, Université Paris Dauphine, 6 juin.

2018, *Micro-work, artificial intelligence and the automotive industry*. Atelier *A new industrial revolution? Labor, technology and the automotive industry*. Ecole Sant'Anna d'Etudes avancées, Pisa, IT, 31 mai.
inter-level feedback loops, as individuals remain separate from firms for all practical purposes; while in those that represent multi-layer platforms, firms influence individuals but not the other way round. Analysis of economic network structures suffices to obtain these results, abstracting from any personal relationships that workers (or clients) may have with their peers. Even beyond the specific context of the platform, this suggests that the social network of peers and friends does not suffice to establish whether labor is (or is not) embedded, without also commenting on the economic network of organizations to which workers are tied in various ways.

Future research will have to establish the conditions under which, metaphorically, the number of layers matters more than the number of friends — that is, the economic structure of outsourcing ties affects workers’ conditions and outcomes more than their social networks of peers. In online labor, this occurs to the extent that peer networks of workers rarely exist. Siloed platform designs often limit their opportunities to interact with other workers (Gray et al., 2016), and sometimes, platform management tightly controls the few interaction spaces they have, such as web-based discussion forums (Casilli et al., 2019). They do not even have the comfort of sharing their experience with their family, friends, or other people in their broader social environment (sub-section 5.3). Because over-supply of labor and globalization lead to price competition, workers have limited opportunities to organize collectively, and “mostly interact as competitors rather than collaborators” (Graham and Anwar, 2019). Under these conditions, the interactions that matter are those that occur in the economic layers that embed the worker. It would be interesting to see, then, if initiatives to support the creation of independent, non-platform-controlled networking spaces for workers (such as online discussion forums) mitigates or even reverses this effect.

The discovery of deep embeddedness in the case of multi-layer platforms is evidence of the merits of the multi-level view, which completes and refines the conclusions derived by Wood et al. (2019b) based on Peck (2013)'s distinction between hard and soft Polanyi. In the case of marketplace-like platforms (section 5.3), I have made the same claim of disembeddedness that they insist upon. The difference is that they impute this result to commodification (in the hard-Polanyi sense), while I base my argument on the thinness of affiliation ties between individuals and firms (I-F). In this respect, the proposed multi-level view is entirely consistent with a broad view of embeddedness and can smoothly integrate the hard and soft dimensions in one common scheme. In sum, far from weakening the grandiose view that pervades Polanyi's work, the network perspective inaugurated with the seminal article of Granovetter (1985) does have potential to advance this program of research. Future studies of embeddedness – regardless of their specific setting – should combine the Polanyian and Granovetterian perspectives, provided the latter is re-interpreted in multi-level perspective.

Of course, this paper has limitations, and the main one is the small empirical basis on which the analysis is based. It does not allow extending conclusions to platforms that do not offer labor mediation services (for example, social media such as Facebook or Twitter), and with its focus on France, it may have missed some forms of platform-enabled outsourcing organizations. For example in the Global South,
2018, *Deference networks and knowledge-building in the “sharing” economy*. S&O Research Day, HEC Paris, 24 mai.

2018, *The elephant in the dining room: Digital platforms and the restaurant industry* (avec J. Posada). *Digital Economy Conference*, King's College, Londres, GB, 11 mai.

2017, *Whose results are these anyway? Negotiating diverging agendas after SNA research*. Atelier RECSNA17, Paris, 5 déc.

2017, *Inconspicuous digital labor and online quality valuations: A French restaurant booking and rating platform (avec J. Posada). Conférence Reshaping Work in the Platform Economy*, Amsterdam, NL, 19 oct.

2017, *Leaders in the collaborative economy*. Conférence EUSN2017, Mayence, DE, 29 sept.

2017, *Dyadic analysis of migration flows across Italian provinces*. EUSN2017, Mayence, DE, 27 sept.

2017, *Algorithmes et travail*. Atelier *Le pouvoir des algorithmes*, MSH Paris-Saclay, 21 juin.

2017, *Social networks in the collaborative economy: the making of a sector and its norms*. XXXVI Conférence INSNA Sunbelt, Pékin, CN, 4 juin.

2017, *Social networks and norms in the collaborative economy*. Séminaire, Université Paris Sud, 11 mai.

2017, *Mapping the collaborative economy: from platform capitalism to social innovation*. Conférence annuelle de *British Sociological Association*, Manchester, GB, 6 avr.

2017, *Networks, status and knowledge in the collaborative economy*. Atelier *Multilevel Networks*, Sciences Po, Paris, 1 mars.

2016, *Le phénomène ‘pro ana’ : Troubles alimentaires et réseaux sociaux*. Séminaire, UQAM, Montréal, CA, 2 nov., et Université Laval, Québec, CA, 8 nov.

2016, *Le sociologue dans la cité connectée* : Une expérience d'articulation entre éthique, science et politique. Congrès *Association Internationale des Sociologues de Langue Française* (AISLF), Montréal, CA, 5 juil.

2016, *The visual sociogram in qualitative and mixed-methods research* (avec L. Ryan). Conférence EUSN2016, Sciences Po, Paris, 15 juin.

2016, *Communities and collaboration in the digital world: an ‘ethno-computational approach’ through social networks*. Séminaire, Université Paris Sud, Orsay, 25 mars.

2016, *Sociabilité et soutien social dans les communautés en ligne autour des troubles de l'alimentation* (avec A.A. Casilli). Séminaire, EHESS, Paris, 15 mars.

2016, *Peer effects and performance similarity in organizational networks: A longitudinal study*. Séminaire, Université de l'Insubria, Varese, IT, 8 mars.

2015, *Réseaux sociaux, communautés en ligne et troubles alimentaires*. Colloque *Mutations Alimentaires*, CNRS, Paris, 18 sept.

2015, *Persistence and turnover in online communities: Five years of the French webosphere on eating disorders*. XXXV Conférence INSNA Sunbelt, Brighton, GB, 27 juin.

2015, *Recent improvements in data access in Europe* (avec R. Silberman). 2nd *European Data Access Forum*, Eurostat, Luxembourg, LU, 24 mars.

2015, *La visualisation des données : Des instruments, et un regard critique*. Séminaire, Université de Toulouse Jean Jaurès, Toulouse, 19 mars.

2015, *Sociabilité et soutien social dans les communautés en ligne autour des troubles de l'alimentation*. Séminaire, Université de Toulouse Jean Jaurès, Toulouse, 13 mars.

2015, *Peer effects and performance similarity in organizational networks*. Séminaire, Université de Milan – Bicocca, Milan, IT, 25 fév.
there may be more mingling of platform labor with traditional business-process-outsourcing services. Nevertheless, I believe the insight provided here contributes to the (growing, but still scant) literature on platform labor, has value as an example of fruitful cross-disciplinary research, and offers a fresh perspective on embeddedness.

## 7 Acknowledgements

The data used in this paper are from the DiPLab ("Digital Platform Labor") research project, co-funded by Maison des Sciences de l'Homme Paris-Saclay; Force Ou-vrière, a workers' union, through IRES (Social and Economic Research Institute); and France Stratégie, a service of the French Prime Minister. Foule Factory - Wirk offered logistical and financial support for fielding the survey, and Inria provided complementary funding. For more information: http://diplab.eu/

I am grateful to Antonio A. Casilli, Anoush Margaryan and Florian Schmidt for inspiring discussions that helped shape the arguments developed in this paper. A preliminary version of this paper was presented in a thematic session on "Networks of Economic Life: Relational Processes Within Economic Organizations and Markets" at the INSNA Sunbelt Conference 2019. I thank organizers and participants for helpful feedback. Any remaining errors or inconsistencies are exclusively mine.

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## Conférences et interventions publiques de vulgarisation (sélection 2015-19)

2019, Le Micro-Travail en France : derrière l'automatisation, de nouvelles précarités au travail ? (avec A.A. Casilli) CFE-CGC Orange, Paris, 1 juil.

2019, Le Micro-Travail en France (avec A.A. Casilli). Fondation Gabriel Péri, Paris, 26 juin.

2019, Big data et société : vie privée, travail, inégalités. Présentation invitée, conférence « La vie publique de vos données personnelles », Banque de France, Paris, 6 juin.

2019, Données massives en recherche. Table Ronde, Polethis – Institut Imagine, Paris, 15 mai.

2019, Sélectionné.e par une IA ? Algorithmes, inégalités, et les « humains dans la boucle ». Séminaire, Centre D'Alembert, Orsay, 18 avr.

2019, GAFAM : Défis et alternatives. Table ronde, Assemblée Nationale, Paris, 21 mars.

2018, Recherche et social data : un point à l'heure des restrictions. Table ronde, Social Media Club, Paris, 14 nov.

2018, *Online platform labour*. Présentation invitée à EIT Digital, Rennes, 14 nov.

2018, Derrière une crise, s'en cache une autre: que font les données numériques aux sciences sociales. Présentation invitée, *Databeers* Paris, 6 nov.

2018, Les promesses et les périls du travail sur plateformes. Table ronde, France Stratégie, Paris, 6 juil.

2018, Faut-il interdire la parole problématique en ligne ? Présentation invitée au congrès médical GEPS, Montpellier, 12 jan.

2017, *Open data*. Table ronde, Conférence *Science and You*, McGill University, Montréal, CA, 5 mai.

2016, Vers une économie collaborative sociale et solidaire ? Présentation invitée, Ministère de l'Economie, Paris, 13 déc.

2016, *Big data*. Animation de deux ateliers étudiants au Forum International Science et Société, Québec, CA, 4-6 nov.

2016, *Big data*, que fait-on de nos données ? Table ronde, Musée de la Civilisation, Québec, CA, 3 nov.

2016, L'économie peut-elle être collaborative ? Interview, L'Esplanade, Montréal, CA, 2 nov.

2016, Sommes-nous tous des digital laborers ? Présentation invitée, salon *Autonomy*, Paris, 8 oct.

2016, Les réseaux sociaux et leurs utilisations par les personnes souffrant de TCA. Présentation invitée au congrès de l'association ACM pour les troubles alimentaires, Nîmes, 5 fév.

2015, Accompagnement numérique et santé. Présentation invitée au Forum du Crédit Municipal de Paris, 8 oct.

2015, Communautés en ligne et troubles alimentaires. Présentation invitée à la journée famille de la Fédération nationale des associations sur les troubles des conduites alimentaires, Paris, 12 juin.

2015, *Il fenomeno 'ana-mia': frequentazione patologica o luogo di supporto*. Présentation invitée au congrès des associations italiennes sur les troubles alimentaires, Portogruaro, IT, 9 mai.

2015, Les données : quelle révolution pour notre quotidien ? Table ronde, Printemps de l'Economie, Ministère de l'Economie, Paris, 17 avr.

## ENSEIGNEMENT

Depuis juil. 2015, *Senior Fellow of the Higher Education Academy* (qualification britannique reconnaissant un rôle de leadership dans l'enseignement supérieur).
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## Activités d'enseignement supérieur correspondant à crédits (sélection, depuis 2015)

<table><thead><tr><td>Années</td><td>Cours (niveau)</td><td>Rôle</td><td>Etablissement</td><td>Heures</td><td>Langue</td></tr></thead><tbody><tr><td>2018-20</td><td>Science des réseaux sociaux et économiques (M2)</td><td>Enseignante co-responsable</td><td>ENSAE, Paris-Saclay</td><td>24h CM/an</td><td>FR</td></tr><tr><td>2014-20</td><td>Sociologie des réseaux sociaux (M2)</td><td>Enseignante responsable</td><td>EHESS / ENS, Paris</td><td>24h CM/an</td><td>FR</td></tr><tr><td>2017-20</td><td>Projet incubateur (M2)</td><td>Chargée de TD</td><td>Télécom Paris</td><td>24h TD/an</td><td>FR</td></tr><tr><td>2016-20</td><td>Méthodes de recherche (D)</td><td>Enseignante responsable</td><td>Université de l'Insubria, Varese, IT</td><td>15h CM/an</td><td>EN</td></tr><tr><td>2014-17</td><td>Sociologie du monde numérique (M2)</td><td>Intervenante externe invitée</td><td>Arts et Métiers ParisTech, Paris</td><td>6h CM/an</td><td>FR</td></tr><tr><td>2014-16</td><td>Méthodes de recherche (D)</td><td>Enseignante responsable</td><td>Université de Greenwich, GB</td><td>9h CM/an</td><td>EN</td></tr><tr><td>2014-16</td><td>Simulation informatique de la communication politique (M2)</td><td>Intervenante externe invitée</td><td>Université Libre de Berlin, DE</td><td>2h CM/an</td><td>EN</td></tr><tr><td>2014-15</td><td>Tendances de la recherche (M2)</td><td>Intervenante externe invitée</td><td>Université de Toulouse Jean Jaurès</td><td>6h CM</td><td>FR</td></tr><tr><td>2012-15</td><td>Economie de l'entreprise (M)</td><td>Enseignante responsable</td><td>Université de Greenwich, GB</td><td>30h CM/an</td><td>EN</td></tr></tbody></table>

## Activités d'enseignement supérieur correspondant à crédits (avant 2015, synthèse)

2010-14, Université de Greenwich, GB : Méthodes des sciences sociales (TD), Préparation au mémoire de master (CM, TD), Analyse des réseaux sociaux (TD), Enjeux de la mondialisation (TD), Entreprise globale et innovation (TD).

2012-13, Université de la Suisse Italienne, CH : Réseaux sociaux et organisationnels (intervenante externe invitée, 2 CM de 3h).

2012, ABRS Hong Kong, HK : Entreprises multi-nationales (TD).

2001-06, Université de Cergy-Pontoise : Economie descriptive (TD), Microéconomie I (TD), Economie publique (TD), Macroéconomie I (TD), Macroéconomie ouverte (TD).

## Encadrement de doctorants

2012-17, Y. Sarabi, Université de Greenwich, GB.

2014-18, H. Minh Luong (co-direction), Université de Greenwich, GB.

2014 – (soutenance prévue en 2019), A. Piazza (co-direction), Université de Greenwich, GB.

## Encadrement de mémoires de master

2015-19, M2 Sociologie et Statistique, EHESS/ENS (6 étudiants dont 5 ont déjà soutenu).

2018-19, M2 Sociologie quantitative et démographie, ENSAE (3 étudiants, tous ont soutenu).

2018-19, M2 *Master in Economics*, ENSAE (1 étudiant, co-direction, en cours).
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Granovetter, M. e. (2004). Polanyi symposium: A conversation on embeddedness.
*Socio-Economic Review*, 2(1):09–135.

Gray, M. and Suri, S. (2019). *Ghost Work: How to Stop Silicon Valley from Building
a New Global Underclass*. Houghton Mifflin Harcourt.

Gray, M., Suri, S., Ali, S., and Kulkarni, D. (2016). The crowd is a collaborative network. In *Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing*, pages 134–147.

Gulati, R. and Gargiulo, M. (1999). Where do interorganizational networks come
from? *American Journal of Sociology*, 104(5):1439–1493.

Hara, K., Adams, A., Milland, K., Savage, S., Callison-Burch, C., and Bigham,
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forms. *Work, Employment and Society*, 33(1):21–38.

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hotel industry. *American Journal of Sociology*, 106(2):387–423.

Krippner, G. R. (2002). The elusive market: Embeddedness and the paradigm of
economic sociology. *Theory and Society*, 30(6):775–810.

Lazega, E. (2016). Synchronization costs in the organizational society: Intermediary
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and Snijders, T., editors, *Multilevel Network Analysis for the Social Sciences:
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Murali, A. (2019). How India’s data labellers are powering the global AI race.
*Factor Daily*.

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Origins of Our Time*. Beacon Press.
2010-14, Master Economie et finance d'entreprise, et Master Gestion internationale, Université de Greenwich, GB (20 étudiants).

## Encadrement de stages

2019, LRI, 1 étudiante L3.

2017-18, LRI, 1 étudiante L3 et 1 étudiant M2.

2016-17, LRI, 1 étudiante L3 et 1 étudiant M2.

2016-17, Télécom ParisTech, 2 étudiantes M2 (co-encadrées avec A.A. Casilli).

## Participation à jurys de thèse

2019, L. Rua (directeurs : M. Razafindrakoto et F. Roubaud), économie, IRD.

2019, S. Balech (directeur : C. Benavent), gestion, Université Paris Nanterre.

2018, V. Barbet (directrice : J. Rouchier), économie, Aix-Marseille Université.

2015, N. Gailliard (directeur : O. Barreteau), informatique, IRSTEA, Montpellier.

2014, A. Defossez (directrice : M.-P. Bès), sociologie, Université de Toulouse Jean Jaurès.

2011, L. Wang (directeur : A. Lomi), gestion, Université de Suisse Italienne, CH.

## Autres participations à jurys

2014-17, Examinateur externe, Programme de formation pre-doctorale en sciences sociales, University College London (UCL), Londres, GB.

## Enseignement en formation continue (sélection)

2018, Intervenante invitée, Ecole thématique CNRS « Analyse des réseaux sociaux et complexité », Cargèse (1 présentation plénière sur « Modèles multi-agents et simulations » ; co-animation d'un atelier avec J. Brailly et G. Favre sur « Statistiques de réseaux avancées », 5h).

2018, Intervenante invitée, Ecole d'été en analyse des réseaux sociaux (Université de Greenwich, GB) sur « Ego-network analysis » (3h).

2018, Intervenante invitée, 36ème session nationale de INTEFP, sur « La micro-travail en France : le cas de Foulefactory » (2h), Marcy-l'étoile, 4 juil.

2017, « Introduction à NetLogo et aux modèles multi-agents de réseaux » (avec Y. Sarabi). Stage (6h) pour chercheurs, conférence EUSN2017, Mayence, DE (donné également à EUSN2016, Paris, et Sunbelt 2015, Brighton, GB).

2016, Les enjeux sociaux du numérique. Deux stages (6h chacun) pour représentants syndicaux, ISSTO – Université de Rennes 2.

2015, « Analyse des réseaux sociaux : théories, applications, techniques » (avec Y. Sarabi). Cours intensif (24h) pour chercheurs, Université de Greenwich, GB (proposé également en 2013 et 2014).

2015, « Analyse des réseaux sociaux ». Cours intensif (20h) pour chercheurs, Université de Lund, SE (proposé également à l'Université de Tel Aviv, IL, en 2014).

2015, « Méthodes mixtes en analyse des réseaux sociaux » (avec A. D'Angelo, L. Ryan). Stage (6h) pour chercheurs, Université de Greenwich, GB (proposé aussi en 2014).

2014, « Découvrir l'analyse des réseaux sociaux ». Atelier de découverte (1h30) pour chercheurs, Télécom ParisTech.

2014, « Introduction à l'analyse des réseaux sociaux » (avec Y. Sarabi). Stage (6h) pour chercheurs, Université de Greenwich, GB (proposé aussi en 2013, 2012, 2011 à Greenwich ; en 2014 et 2013 aux conférences Sunbelt de Tampa, US et Hambourg, DE ; et à la conférence UKSNA de Bristol, GB, 2013).
Prassl, J. and Risak, M. (2016). Uber, Taskrabbit, and co.: Platforms as employers? *Rethinking the legal analysis of crowdwork*. *Comparative Labor Law & Policy Journal*, 37(3).

Roberts, S. (2019). *Behind the Screen: Content Moderation in the Shadows of Social Media*. Yale University Press.

Rochet, J.-C. and Tirole, J. (2003). Platform competition in two-sided markets. *Journal of the European Economic Association*, 1(4):990–1029.

Rosenblat, A. (2018). *Überland: How Algorithms Are Rewriting the Rules of Work*. University of California Press.

Rysman, M. (2009). The economics of two-sided markets. *Journal of Economic Perspectives*, 23(3):125–43.

Schmidt, C. (2017). Digital labour markets in the platform economy: Mapping the political challenges of crowd work and gig work. Report, Friedrich-Ebert-Stiftung.

Schmidt, F. (2019). Crowdproduktion von Trainingsdaten: Zur Rolle von Online-Arbeit beim Trainieren autonomer Fahrzeuge. Report, Hans-Böckler-Stiftung.

Snijders, T. and Bosker, R. (2011 (1999)). *Multilevel Analysis: An introduction to basic and advanced multilevel modeling*. Sage.

Srnicek, N. (2016). *Platform Capitalism*. Polity Press.

Sundararajan, A. (2016). *The Sharing Economy: The End of Employment and the Rise of Crowd-based Capitalism*. MIT Press.

Tubaro, P. and Casilli, A. (2019). Micro-work, artificial intelligence and the automotive industry. *Journal of Industrial and Business Economics*, 46(3):333–345.

Uzzi, B. (1996). The sources and consequences of embeddedness for the economic performance of organizations: The network effect. *American Sociological Review*, 61(4):674–698.

Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. *Administrative Science Quarterly*, 42(1):35–67.

Vaughan, J. (2018). Making better use of the crowd: How crowdsourcing can advance machine learning research. *Journal of Machine Learning Research*, 18(193):1–46.

Wasserman, S. and Faust, K. (1994). *Social Network Analysis: Methods and Applications*. Cambridge University Press.

Williamson, O. (1975). *Markets and Hierarchies: Analysis and Antitrust Implications*. Free Press.

Williamson, O. (1981). The economics of organization: The transaction cost approach. *American Journal of Sociology*, 87(3):548–577.

Wood, A., Graham, M., Lehdonvirta, V., and Hjorth, I. (2019a). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy. *Work, Employment and Society*, 33(1):56–75.

Wood, A., Graham, M., Lehdonvirta, V., and Hjorth, I. (2019b). Networked but commodified: The (dis)embeddedness of digital labour in the gig economy. *Sociology*, page (online first).
# DIVERS

## Présence média

2019, BBC World Service, Le journal du CNRS, AFP/L'Express, Radio France Inter (interviews) ; Le Monde, La Tribune, Les Echos, La Croix, Alternatives Economiques, Sud-Ouest, Digital Society Forum (comptes rendus).

2018, CNRS Puits de Science (vidéo-interview) ; La Stampa, GEO Ado, Qu'est-ce qu'on fait, L'Édition-Université Paris-Saclay (interviews) ; Les Echos, Ent'revues, Le Monde (comptes rendus).

2017, Le Monde, Le Temps, Le Devoir, La libre Belgique (interviews), Les Echos, PourquoiDocteur (mentions).

2016, Le Monde, Journal International de Médecine, L'obs/Rue89, Mashable/France24 (comptes rendus d'ouvrage), Radio France Culture, Radio France Inter, ICI Radio Canada, Radio Aligre.fm (tables rondes), Slate.fr (interview).

2015, Europe1, Deutsche Welle (interviews) ; France 24, RTL, L'Express, Vice, PourquoiDocteur, Numérama, Ouest France, Le Figaro, Santé Magazine, The Daily Beast (mentions).

2014, Le Monde, SkyTG 24 (interview) ; Le Temps, Arte, Le Soir, France Info, Wired Italia (mentions).

2013, Radio France Culture, Radio Aligre FM (tables rondes), La nouvelle édition (Canal +), Elle, Femme Actuelle, Le temps, SFR Player (interviews) ; Sciences Humaines, Washington Post (mentions).

2012, BBC Radio 3 (présentation orale de 15 minutes, « The Essay ») ; Voice of Russia (table ronde) ; Nouvel obs (interview).

2011, OWNI, Regards sur le numérique, Woman's journal (interviews) ; Le soir d'Algérie, CNN, The Daily Mail, Technorati, GigaOM, The Times of India, Zee News TV India, Oman Tribune, Tempo Indonesia, Science Daily, Sciencenewsline (mentions).

## Compétences informatiques

Bureautique : Système Windows ; MS Office ; OpenOffice ; LaTeX, Overleaf ; Internet, email, systèmes d'Intranet.

Construction de sites web : CMS,Wordpress.

Logiciels statistiques et d'analyse des données : R, Python, Stata.

Analyse des réseaux : Ucinet-Netdraw, Gephi, RSiena, R-sna, R-igraph, R-statnet.

Modélisation multi-agents : NetLogo.

Logiciels pour l'enseignement : Moodle, Turnitin.

## Compétences linguistiques

Italien : langue maternelle ; Français : bilingue ; Anglais : bilingue ; Allemand : courant ; Espagnol : bases.
Yin, M., Gray, M., Suri, S., and Vaughan, J. (2016). The communication network within the crowd. In *Proceedings of the 25th International Conference on World Wide Web*, pages 1293–1303.
<figure><img src="image_8.png" /></figure>
# Festival attendance as a network of attention:
A case study in the sharing economy

Paola Tubaro

## Abstract

I show that one mechanism through which business events contribute to configuring the shared values of a community is attention – the way in which people allocate their cognitive effort and time. Using a festival of the “sharing economy” as a case study, I construct the set of choices of whom to pay attention to as a network, and I explain its structure with exponential random graph models (ERGM). I find two critical processes underpinning it: a quest for non-redundancy, or novelty, which may go as far as overriding any status effects, and a strategic use of popularity and reciprocity, as ways through which, depending on commonalities with others and on situations of competition, individuals endeavor to adjust their position in the pecking order. These compound that processes result from combinations of simpler mechanisms, can explain how attention-paying choices may engender complex patterns of domination through which different actors and values may gain, lose or maintain legitimacy.

**Key words:** Events, economy of attention, social networks, ERGM

## 1 Introduction

A growing literature has emphasized how events such as music awards (Anand and Watson, 2004), literary prizes (Anand and Jones, 2008), book fairs (Moeran, 2011) and film festivals (Smits, 2018) call to mind the metaphor of “tournaments of value” that Appadurai (1986, p. 21) coined to describe the Melanesian *kula* ring :

<footnote>Laboratoire de Recherche en Informatique, Centre National de la Recherche Scientifique, Paris Saclay, e-mail: paola.tubaro@lri.fr</footnote>
Complex periodic events that are removed in some culturally-defined way from the routine of everyday economic life. Participation in them is likely to be both a privilege for those in power and an instrument of status contests between them [...] What is at issue in such tournaments is not just status, rank, fame, or reputation of actors, but the disposition of the central tokens of value in the society in question.

What all these events have in common is that they bring together and render visible “imagined communities” (Anderson, 1983) through periodically recurring (albeit temporary) physical co-location. They contribute to giving cognitive legitimacy to an area of activity, making it real and consequential to participants. Their powerful symbolic structure often “takes the form of a public spectacle” (Anand and Watson, 2004, p. 60) with carnival-like elements (Moeran and Pedersen, 2011, p. 5). Events shape collective identity, helping participants define what is shared among them, what should be considered as worthy, where the boundaries with the external world lie. Depending on the circumstances, events may strengthen the dominant values (if any) or challenge them: Delacour and Leca (2011) refer to these two cases, respectively, as “tournaments of value” in the singular and “tournaments of values” in the plural.

The literature on creative industries engages most explicitly with the trope of tournaments of value(s) (or, as Anand and Watson (2004) and Anand and Jones (2008) put it, “tournament rituals”). Management scholars prefer to call them “field-configuring events” (Lampel and Meyer, 2008) and social anthropologists “large-scale professional gatherings” (Leivestad and Nyqvist, 2017), referring to a wider range of settings from policy (Hardy and Maguire, 2010; Schüssler et al., 2014) to high-tech industries (Aspers and Darr, 2011). Despite terminological differences, there is large consensus on the role of events in defining shared values, broadly interpreted as the criteria by which people judge what is legitimate (Suchman, 1995, p. 574). According to Moeran and Pedersen (2011), the idea of tournaments of value(s) covers about the same ground as that of field-configuring events. Either way, focus is on institutionalization of a shared culture and formation of the behavioral scripts that allow actors to be seen by others as legitimate (Aspers and Darr, 2011). Following Simmel’s idea that values are judgements made by people, Moeran and Pedersen (2011, p. 10) sees events as the sites where values are given: not only economic values that result from negotiations, but quality and legitimacy judgements made collectively by members of the concerned community.

While the literature has convincingly shown *that* tournaments do inflect values, it has only scratched the surface of *how* they do so – how tournaments work in practice. If many scholars – from Anand and Watson (2004) to Moeran (2011) – emphasize the importance of networking as a way through which participants collectively negotiate, define and revise values, rare are those who apply formal social network analysis methods to unpack the underlying social mechanisms, like reciprocity or clustering. Brailly et al. (2016) and Favre and Brailly (2015) do so without recurring to the metaphor of tournaments, but come close to it by leveraging Selznick (1957)’s notion of “precarious values”. A value is precarious when it is at risk of losing its carriers and representatives – that is, the active support of relevant individuals or groups that help preserve it against competing values. Thus, mapping
networks of people who carry different values helps detect patterns of domination
that eventually impose some values and marginalize others.

To advance this line of research, it is important to acknowledge the effects of
differences in the material infrastructure and technical organization of events (Urry,
2003). Informal networking matters most in trade fairs (Brailly et al., 2016; Brailly,
2016; Favre and Brailly, 2015; Moeran, 2011; Panitz and Glückler, 2017), that is,
business events where sellers hold stands that buyers visit and most interactions are
one-to-one, private meetings that participants arrange autonomously and often in-
formally – although event organizers sometimes provide software applications or
other services to facilitate contacts. Negotiations started at the event may afterward
lead to signature of contracts between the companies of the buyer and the seller
(Brailly et al., 2016) – whereby an initially informal interaction becomes formal.
The nature of interactions differs in events shaped as *conferences*, which consist
of multiple, sometimes parallel sessions (whether they be talks, panels, workshops
etc.). In these settings, participants exchange ideas rather than goods, and interac-
tions occur mainly through *attendance*. It is by attending (for example) a panel that
participants become aware of the ideas of the speakers, weigh them against their
previously held knowledge and beliefs, and have the opportunity to ask questions.
Interactions can be schematized as one (session) to many (members of the audi-
ence), and publicly visible to all attendees. While the conference organizers’ choice
of topics, speakers, schedule and venues constrains participants’ options, there is
also an important element of decentralization as participants autonomously choose
what to attend from a given event program.

What shapes attendance decisions in conference-like settings? Oddly, this ques-
tion has received hardly any scholarly attention so far, despite the diffusion of the
conference format – sometimes as a standalone event (Forrest, 2017), sometimes on
the side of trade fairs (Favre and Brailly, 2015). The organization of festivals often
resembles that of conferences too (Arcodia and Whitford, 2006). This paper is a
first step toward addressing this question, shedding new light on the mechanisms
that drive participants’ choices.

I frame attendance as the *outcome of individual decisions of what (and more
specifically, whom) to pay attention to* in a conference setting. I rely on Goldhaber
(1997)'s definition of the conference as a small-sized, closed, temporary economy
of attention, as he presented it as part of his keynote at a, well, conference:

> While you are here, your main concern is how you pay attention and where you pay it [...]
> Even between sessions, the exchange of attention is what mostly tends to occupy people at
> a conference. Of course, there are material considerations [...] But they tend to be secondary
> issues, taken for granted, and not occupying much attention. We are living a temporary
> attention economy in miniature right at this moment.

This perspective enriches our understanding of events as tournaments of value(s)
with ideas on the economy of attention, supporting the claim that the choice of what
/ whom to pay attention to is one of the mechanisms through which tournaments
take place. Although the processes I pinpoint in what follows are derived from a
single case study – that of the OuiShare Fest, a festival in the so-called “sharing
economy” – they provide insights of potentially wider applicability. I argue that
paying attention to sessions or speakers that defend precarious values *à la* Selznick (1957) is a way to support them; turning one's attention to alternative speakers challenges or dismisses them. Thus, attention relationships are one way in which tournaments unfurl, so to speak. I model these relationships as a network to highlight the way they breed interdependencies across actors and sustain alliances, conflicts, and the emergence of hierarchies. My findings invite to see them as channels through which different actors and values gain, lose or maintain legitimacy, and contribute to engendering patterns of domination that may have far-reaching effects – possibly beyond the specific event attended.

## 2 A “Sharing Economy” event

The OuiShare Fest is an international event that a non-profit organization of the same name organized every year in Paris between 2013 and 2017, with a local edition in Barcelona over 2015-17. It was structured as a conference, with multiple sessions running in parallel (except a few plenary sessions such as Opening and Closure) over three days. OuiShare presented it as follows:

> "OuiShare Fest is an interdisciplinary festival that gathers creative leaders, entrepreneurs, movement builders, purpose-driven organizations and communities from across sectors and countries who want to drive systemic and meaningful change. Though diverse, attendees of OuiShare Fest have many things in common: a willingness to experiment, step out of their comfort zone, collaborate and connect with other humans in a profound way".

OuiShare and its Fest were created in the wake of enthusiasm for what came to be called the “sharing economy” in the early 2010s (Schor and Cansoy, 2020). The rapid popularity of the “sharing” (or alternatively “collaborative”, see Botsman and Rogers (2010)) label stemmed from its entrenched promise of societal change in addition to digitization and technological innovation. OuiShare and other associations such as Shareable in the USA, and ShareNL in the Netherlands, explicitly leveraged these aspirations to federate stakeholders’ actions and to promote (some version of) this agenda. Surely, the socially engaged flavor of sharing economy discourses sparked controversy, and some saw it as a cover for mere commercial transactions (Slee, 2015), with forms of discrimination (Schor and Attwood-Charles, 2017) and degrading working conditions (Rosenblat and Stark, 2016; Ravenelle, 2019). Nonetheless, many users still see the sharing economy as a means to develop a morally acceptable exchange system, a sense of community, and meaningful working lives (Fitzmaurice et al., 2018).

In what follows, I motivate my choice of the OuiShare Fest as an ideal setting to study how attention choices shape values in a nascent area of socio-economic activity that strives for legitimacy. I then explain how I operationalize the notion of attention-paying.
## 2.1 The OuiShare Fest as a mini-economy of attention

The OuiShare Fest can be seen as a small-sized, temporary economy of attention as suggested in section 1. Participants did not (and did not intend to) constitute a market or an industry, did not take the role of buyers or sellers, and did not trade: the event was about ideas, not goods. Its core was a rich program from which participants chose what to attend. Every year, the program included manifold session formats, ranging from classical keynotes and panels to interactive workshops and more innovative fishbowls, games, shows, artistic performances and even “unconferences” and “unpanels”. Some sessions took place in traditionally-arranged conference rooms, others in more extravagant venues such as a boat and a tent. Program preparation took several months prior to the event, and resulted both from the organizers’ own choices and from submissions to an open call for session proposals. Once all speakers (also including chairs, moderators, facilitators, performers etc.) and sessions had been scheduled, the organizers aggregated them into thematic tracks, each distinguished by a different color, so that participants could more easily navigate the program and make their attendance choices.

The Annex reports the list of themes for each year of the Paris edition. These themes define the scope of the event as understood by the organizers, and as implicitly agreed to by all those who chose to participate. Their designation and the labels attached to it are an attempt to categorize the sharing economy at a given point in time, assigning priorities and differentially giving legitimacy to specific areas of activity and expertise. Of note, themes denote value cleavages. For example, personal development is an area beloved by many, but frowned upon by others; similarly, decentralization principles arouse the enthusiasm of some and the skepticism of others. Thematic interests are thus indicative of the standing of each speaker in the tournament that the event represents.

That thematic tracks changed over time is in itself a sign of the evolution of legitimacy criteria within this community. Some differences are minor and depend on overall design (for example, number of themes included each year) or terminology (the 2016 “Education & Personal Development” covering about the same contents as “Presence & consciousness” in 2017). Other differences are substantive. “Collaborative consumption”, the term launched by Botsman and Rogers (2010), was prominent at start and disappeared afterward. The city became more and more important, becoming the overarching theme of the 2017 event (“Cities of the world, unite!”). Blockchain and decentralization rose between 2015 and 2016, and vanished in 2017. At each edition, OuiShare took into account the lessons learned from the previous year’s experience to update its offer – that is, in addition to exogenous influences, the outcomes of past tournaments contributed to shaping each new tournament.
## 2.2 Networks of speakers and attendees

The attractiveness of the OuiShare Fest program was embodied in the choice of speakers<fnref n="1" />. Formally, participants chose sessions to attend, but ultimately, it was to speakers that their choices were directed. Sessions' titles and contents mirrored the knowledge and interests of those who contributed to them. Speakers were from multiple backgrounds (such as start-up founders, technology specialists, business consultants, policy-makers, academics, charity champions, and artists) and had expertise in diverse areas (the themes discussed above, subsection 2.1). They carried with them different views of the sharing economy, political orientations, cultural norms and values, which they endeavored to convey to participants.

In 2016, speakers constituted about 17% of all participants – against 12% team members, 5% press and 66% non-speaking attendees. As in other events, theirs was a privileged position reserved to a minority (Favre and Brailly, 2015) and made visible to all through a differentiated name tag. Among other things, speakers were entitled to free entrance throughout the duration of the event. They enjoyed high visibility: they all had a profile on the Fest's web page, their talks were advertised to prospective participants through mailing lists and newsletters, they were live-streamed and live-tweeted, and videos were posted online after the event. They were cherished for bringing prestige and epistemic authority: a well-known speaker could not only attract attendees but also raise the standing and respectability of the event.

On this basis, I operationalize choices to pay attention as human relationships between participants and speakers, which can be represented and analyzed with the formalism of graph theory, as is commonly done in social network analysis. This approach is useful to measure and visualize the interdependencies that link actors at the OuiShare Fest, and builds on a rich literature to derive insight into the forces that shape these interdependencies (Amati et al., 2018; Lazega and Snijders, 2016; Lusher et al., 2013). Specifically, the left panel of Figure 1 represents attendee-to-speaker (A2S) relationships as a graph whose nodes are individuals and ties indicate attention choices. The A2S network has “two-mode” structure in that nodes can be either senders (A, attendees) or receivers (S, speakers) of attention ties, but not both. The graph is valued (attendee $A_i$ may choose to attend one or more sessions of speaker $S_j$) and directed (mutual attendance may not occur).

Speakers were themselves also participants and, outside the session(s) assigned to them for their talks (or exhibitions, performances, workshops etc.), they could choose to spend their free time at the event by attending sessions of other speakers. Besides spreading their own message, they could listen to the messages of others. It becomes then particularly interesting to ask *who, from among speakers, paid attention to whom*. Put differently, paying-attention choices can also take the form of

<footnote n="1">¹ In what follows, I use this word to cover all roles of those responsible for at least part of the contents of a session, whether they be keynotes, panelists, round table moderators, workshop facilitators, exhibitors, or performers. Similarly, I call “attendees” all those who were not speakers, whether they registered as attendees, press or team (the latter group included OuiShare members and other volunteers who helped the organizers). “Participants” are all those who took part, both speakers and attendees.</footnote>
speaker-to-speaker (S2S) relationships. The central panel of Figure 1 is the S2S at-
tendance graph, which is valued, directed, and one-mode (any node may be sender
and/or receiver of an attendance tie).

Juxtaposed, these two graphs form a richer, “multi-level” network structure
A2S2S driven by two sources of agency, whereby speakers’ choices are taken as sep-
arate from attendees’ choices (right panel in Figure 1) Lazega and Snijders (2016).

<figure><img src="image_9.png" /><figcaption>**Fig. 1** Left: attendee-to-speaker two-mode network A2S, where black squares are speakers (S), cyan circles are non-speaking attendees (A), and light gray lines are attention-paying choices (of A toward S). Center: speaker-to-speaker one-mode network S2S, where black squares are speakers, black lines are attention-paying choices (of S toward another S, excluding self-loops). Right: multi-level combination of both A2S2S.</figcaption></figure>

S2S relationships are particularly interesting because as noted above, speakers
constituted the core and soul of the OuiShare Fest program and were a selling point
that organizers used to attract registrations. By paying attention to one another, they
could mold the take-home messages of the event, profoundly affecting participants'
understandings and their sense of being part of a common enterprise. Because the
way they chose to direct their attention could have far-reaching consequences on the
survival of the values they embodied, I make them the focus of the remainder of this
paper.

3 Whom do speakers pay attention to?

While attention networks are uncharted territory, the organizational network anal-
ysis literature suggests four social mechanisms that can provide the foundation for
my subsequent theorizing.
**3.1 Thematic affinity**

People commonly direct their attention to the themes they care for. OuiShare Fest speakers are themselves specialists of some area, topic or theme (say, the blockchain), and may be interested in those other speakers who share the same interests. Similarities facilitate mutual recognition of competences. In the broader network analysis literature, commonality of interests and of areas of expertise is known to trigger connections of some sort – an instance of the principle of “homophily” (McPherson et al., 2001).

In a setting like the OuiShare Fest, thematic affinity can drive choices for two reasons. Paying attention to a speaker who is an expert in one's own area is a way to be comforted in one's stances, to see them indirectly confirmed (Centola et al., 2007). It can also be part of an effort to affirm the importance of one's own area of interest and to legitimate its position in a collective undertaking. This is especially true in uncertain situations and in discursive struggles where inclusion of specific areas or categories is ambiguous or contested (Anand and Watson, 2004).

Brought to the extreme, this criterion would sustain the expectation of a fragmented network of speaker-to-speaker (S2S) attention ties consisting of separate cliques defined by areas of interest – with, say, all the blockchain experts attending one another's sessions but not those of the smart city experts, and vice versa (top left panel, figure 2). Reality is likely more nuanced – if only because there can be speakers whose expertise spans different areas and activities.

**3.2 Competition**

Are speakers competitors and when they are, do they pay attention to each other, or rather avoid each other? By “competitors”, I do not mean speakers who are scheduled at the same time in different venues, because they do not necessarily represent mutually exclusive alternatives in the eyes of participants. If their offer differs, they will appeal to distinct audiences. Further, participants have the opportunity to attend one of them live and watch a video-recording of the other afterward.

To define competing speakers, I rather use the social network analysis notion of *positional similarity*. What is relevant here is the A2S2S multi-level participant-to-speaker network (right panel in figure 1), considering all those who pay attention to a given speaker, not just those who are themselves speakers. Two speakers occupy similar – in the limit, identical – network positions (top right panel, figure 2) if they attract essentially the same attendees (whether they are themselves speakers or not) and therefore, display similar patterns of ties in the Fest attention network. Similarity induced by structure is what the literature calls “equivalence” (Lorrain and White, 1971), a notion that goes beyond the mere dyadic level in that two speakers might occupy similar or identical positions without having a tie to each other. The reason why actors with similar ties to others are likely competitors is that they depend on the same resources and face the same opportunities – or re-
sources/opportunities controlled by the same third parties (Burt, 1987; Mizruchi, 1993).

If speakers refuse to pay attention to their competitors, then there will be no ties between them in the S2S network whenever they receive ties from the same others.

<figure><img src="image_10.png" /><figcaption>**Fig. 2** Schematic representation of relational structures resulting from four different social mechanisms. Squares and circles = actors (nodes), lines = choices (ties). **Top left:** a clustered speaker-to-speaker (S2S) network in which choices follow thematic similarities, where node colors represent shared themes. **Top right:** competition resulting from positional similarity in the A2S2S network. Two S nodes represented as black squares and located at the center, receive choices from the same other nodes, including another node of type S represented as a black square, and three of type A represented as cyan circles. **Bottom left:** a centralized S2S network as may result from status-driven choices, with uneven distribution of received choices. Size of nodes is proportional to number of choices received (in-degree). The orange color represents an observable quality: two of the three most chosen nodes have it, while the third receives choices based on popularity effects only. **Bottom right:** an S2S network where all choices are directly reciprocated.</figcaption></figure>
### 3.3 Status

Regardless of themes, topics and competitive positions, people may just follow perceived patterns of domination and direct their attention to speakers with high status. In other words, they may not defend specific “precarious” values (Selznick, 1957), but just align themselves to the values supported by those that they see at the top of the pecking order. If such motivations are intuitively clear, how do people know the pecking order? Indeed, status is difficult to measure owing to its multi-faceted definition. It can be exogenous and derive from some observable quality of individuals: for example, a known professional achievement or an award in a competition. But status can also be endogenous and result from self-reinforcing processes, whereby initially small quality differences between individuals get amplified over time (Manzo and Baldassarri, 2015). This happens when individual qualities are not observable, and actors attribute status to someone based on cues – that may or may not be accurate. In particular, *popularity* is often taken as an indication of better quality, insofar as absence of precise information may drive people to use the choices of others as a guide towards making their own choices. This tendency results in homogeneous, though not necessarily optimal, behavior (Raafat et al., 2009).

Popularity itself may be a reflection of status through feedback loops. The complexity of status stems from its being both an antecedent of network ties – as high-status individuals are more likely to be selected by others – and a consequence of them – insofar as better-connected individuals are ascribed higher status (Torlò and Lomi, 2017). The very relationship that this paper focuses on – paying attention to someone – can be seen as a source of status. A speaker who pays attention to another speaker confers to the latter some degree of honor, respect or prestige. Status can be seen as the accumulation of such acts (Podolny and Phillips, 1996). Like other deference-conferring gestures, attention-paying establishes an ordering or ranking of individuals, and within a bounded setting such as an event, it can be represented as a network (Sauder et al., 2012). This is one reason why status rankings may reinforce themselves and diverge from distribution of observable qualities.

If speakers are more likely to pay attention to other speakers with high status (however construed and operationalized), one should expect to observe an *S2S* network where almost all nodes are directly or indirectly connected to all other nodes, in a centralized structure in which some “stars” receive many choices and the great majority receive very few (bottom left panel, figure 2). There are, however, limits to the pecking order that may result from status-based choices, due to the symbolic “cost” of attending another speaker’s session – the cost of recognizing the others’ status, implicitly admitting that there is something to learn from them (Blau, 1964). This cost may act as a disincentive.