# Case for ecumenical use of network and geometric data analyses in mapping of cultural spaces: Illustration of contemporary French-speaking Swiss theatrical productions

Pierre Bataille, Marc Perrenoud, Robin Casse, Carole Christe, Mathias Rota

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Pierre Bataille, Marc Perrenoud, Robin Casse, Carole Christe, Mathias Rota. Case for ecumenical use of network and geometric data analyses in mapping of cultural spaces: Illustration of contemporary French-speaking Swiss theatrical productions. Poetics, 2025, 110, 10.1016/j-poetic.2025.101999. hal-05002084

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# Case for ecumenical use of network and geometric data analyses in mapping of cultural spaces: Illustration of contemporary French-speaking Swiss theatrical productions

Pierre Bataille<sup>a, *,</sup> , Marc Perrenoud<sup>b</sup> , Robin Casse<sup>c</sup> , Carole Christe<sup>d</sup> , Mathias Rota<sup>e</sup>

## ARTICLE INFO

### Keywords:

- Social network analysis

- Geometric data analysis

- Social structures

- Cultural/linguistic spaces

## ABSTRACT

The cross-use of network and geometric data analyses helps understand how the circulation of symbolic goods is structured. It follows specific logic, intersecting economic and symbolic planes in shaping spaces that do not entirely align with political borders. Both help map circulation spaces and understand their operational logic, aiming to visualize the proximities and/or distances between different places/actors in the production of these symbolic goods. Accordingly, based on several datasets collected to analyze the dynamics that structure contemporary French-speaking Swiss theater production circulation, this article aims to constitute a practical case on the combined use of Social Network Analysis (SNA) and Geometric Data Analysis (GDA) in mapping cultural spaces in a cross-fertilization perspective. The implementation of a mixed SNA and GDA analytical approach reveals distinct clusters of venues based on linguistic boundaries, size, cultural legitimacy, and audience reach. It identifies an "intermediate" subspace, between *avant-garde* and commercial productions. The study highlights methodological advantages in integrating SNA and GDA for developing a nuanced view on cultural dynamics, especially in understanding the career landscape of "ordinary" artists who navigate between artistic autonomy and market demands.

## 1. Introduction

The circulation of symbolic goods and their producers follows specific logic (Gamboni et al., 1987), intersecting economic and symbolic planes in shaping spaces that are not entirely aligned with political borders (Castelnuovo & Ginzburg, 1981). It also arises from the domination dynamics between cultural/linguistic spaces, each in its own temporality and specific logic, as illustrated in the analysis of the circulation of literary works (Casanova, 2004; Sapiro, 2006) or the analysis of the evolution of international scientific collaborations (Maisonobe et al., 2016).

Network and geometric data analyses are useful for mapping circulation spaces and understanding their operational logic. Both aim

E-mail addresses: pierre.bataille@univ-grenoble-alpes.fr (P. Bataille), marc.perrenoud@unil.ch (M. Perrenoud), robin.casse@univ-grenoble-alpes.fr (R. Casse), carole.christe@unil.ch (C. Christe), mathias.rota@he-arc.ch (M. Rota).

<footnote><sup>a</sup> Université Grenoble Alpes, LaRAC, Bâtiment Michel Dubois, Bureau: C114, 1251 Avenue Centrale, FR, 38400 Saint-Martin-d'Hères, France</footnote>

<footnote><sup>b</sup> Université de Lausanne, ISS – LACCUS, Géopolis, Bureau: 5120, UNIL, Mouline, CH, 1015 Lausanne, Switzerland</footnote>

<footnote><sup>c</sup> Observatoire des formations, UGA Bureau 218, Bâtiment PMF, France</footnote>

<footnote><sup>d</sup> Université de Lausanne, ISS – LACCUS, Géopolis, Bureau: 5515, UNIL, Mouline, CH, 1015 Lausanne, Switzerland</footnote>

<footnote><sup>e</sup> Haute école Arc – IMVT, Espace de l'Europe 21, CH, 2000 Neuchâtel, Switzerland</footnote>

<footnote>* Corresponding author.</footnote>
to visualize the proximities and/or distances between different places/actors in the production of these symbolic goods. They enable the definition of spaces and subspaces—both social and spatial—and the analysis of their partition. However, these two methodologies have often been used in opposition to each other or from a cross-confirmation perspective rather than in an articulated and complementary framework. When used together, the focus shifts from characterizing circulation spaces as a whole to differentiating specific elements within the network, where social capital serves as an indicator of position within the studied field (Anheier et al., 1995; Éloire, 2011; Pedrini & Felaco, 2020; Serino et al., 2017).

Our primary focus is here to present an approach that integrates these two methodological perspectives. We introduce an analytical method that is particularly effective in facilitating the interpretation of a network categorized into distinct clusters. The analysis is based on a case study of the circulation of French-speaking Swiss theatrical productions in contemporary Switzerland.

This method allows us to characterize the structure of this circulation space, in a context marked by a significant increase in the number of artists. The performing arts sector in Switzerland has been highly attractive in recent years, driven by a notable process of professionalization (Sutermeister, 2000; Rolle & Moeschler, 2014; Rota, 2022). However, this attractiveness may be contributing to a potential overheating of the system, marked by three key challenges: a limited number of venues, constrained funding opportunities, and heightened competition for audience attention. Such an overheating risks exacerbating the already endemic precariousness of the sector, where artists and companies are often compelled to remain in constant activity to survive, further tilting the balance of power in favor of venues and funders (Rota, 2022). We know how unequally the ability to sustain a career in the arts is distributed among artists, as it depends on the level of recognition they achieve and the quality of their integration into networks of agents who are themselves recognized (Bourdieu, 1980; Lizé, 2016). The analysis method based on clustering sheds light on the positioning of these networks within the French-speaking circulation theatrical productions space. Even though this space is chiastic, as is often the case for artistic fields, the analysis reveals the existence of an intermediate network, positioned at the intersection between a restricted or *avant-garde* production pole and a commercial or artisanal pole. This result constitutes a contribution to the literature on "ordinary" artists: it confirms the existence of varying degrees of consecration (Perrenoud & Bois, 2017, p. 18) within the French-speaking Swiss theatrical productions and highlights the navigation artists might be compelled to undertake across networks to sustain their position in the space.

## 2. From challenging to cross-fertilizing

### 2.1. Social network analysis and geometric data analysis: two ways of defining "proximity"

Visualizing social structures using spatial representation is a practical approach for conducting analysis. This visualization can assume various forms; it may involve projecting information into physical space, using maps to illustrate the organization of social mechanisms, and possibly analyzing the interactions between social and geographical spaces (Ripoll, 2024). Additionally, visualization and mapping cannot directly refer to physical space, but rather to social distances/proximities between individuals and/or institutions. Among these alternative methods for mapping social structures, the most popular are Social Network Analysis (SNA) and Geometric Data Analysis (GDA), which are our primary focus in this paper.

The two methodologies share certain core similarities. Both develop a relational approach to social structures; the position within the obtained mapping reflects a position relative to that of all the entities considered. However, they differ about what it means to be "close" or "distant."

In SNA, mapping is based on observable connections between entities (Mercklé, 2004), which may be direct—such as collaboration and friendship—or indirect—such as co-citation in a bibliography (Milard & Pitarch, 2023) or co-presence in elite clubs (Maclean & Harvey, 2014). The representation of space generally takes the form of a graph (also called a sociogram), where social entities (institutions, individuals, etc.) are the vertices, and the connections between them are the edges. Based on this graph, a series of operations—such as density calculation, clustering algorithms, or block modeling—can be performed to compare the vertices of the sociogram.

Proximity in SNA is derived from the localization of vertices within the sociogram, and can assume two forms. First, vertices are considered close if they belong to the same connected subsets of the graph. These cohesive cliques or clusters partially reflect the shared characteristics of their members, such as attending the same educational institution (Coleman, 1988) or belonging to the same production sector (Larsen & Ellersgaard, 2017). Being part of one of these cliques is also seen as a potential resource (social capital) that can influence access to certain dominant positions (Lin, 2000). Second, vertices are considered close if the structure of their relationships with other entities in the graph is similar—that is, if the vertices are structurally equivalent (Burt, 1995). For instance, vertices that serve as bridges between two cohesive entities share certain characteristics, particularly the ability to provide rare and valuable information to access specific social positions (Granovetter, 1973).

In GDA, proximity is defined as sharing a set of common positions and resources, without necessarily knowing each other at an interpersonal level (Le Roux & Rouanet, 2004). By considering different types of resources—economic, cultural, social, or symbolic capital—the goal is to identify similar profiles that share cultural preferences, political stances, etc. (Lebaron, 2018). Drawing from Bourdieu's (1984) field theory, major oppositions that "objectively" structure the social space under consideration are identified, beyond mere "subjective" representations (Duval, 2013). The statistical tools employed here are factorial analyses, particularly Multiple Correspondence Analysis (MCA), which accommodates categorical variables (Hjellbrekke, 2018). MCA allows individuals to be projected onto a geometric space (typically a two-dimensional plan) using calculations that synthesize a large volume of information about the distribution of various types of resources.

Here, two entities (individuals, institutions, etc.) are considered close if they are located within the same sub-regions of the factorial
plane. Clustering operations or comparisons between different sub-clouds of points can be conducted based on the coordinates along the various axes defining this space. Statistical ellipses are also used to capture the proximities and distances between points and groups of points within the "objective" space of social positions (Le Roux & Rouanet, 2004).

## 2.2. Under the crossfire of criticism

These two forms of mapping have often been presented as oppositional and grounded in seemingly incompatible premises. One of the main criticisms voiced by GDA advocates toward SNA is its tendency to reduce the description of social reality and the notion of "proximity" solely to observable interrelations (Bourdieu, 1980). According to this critique, SNA risks reifying the complexity of processes that underpin social hierarchies and segmentation, much like how some economists limit their analysis to the distribution of economic capital only. GDA, with its "multidimensional" approach, seeks to incorporate various forms of capital—economic, cultural, and social—simultaneously, thus pinpointing positional proximities that are not immediately apparent (Denord, 2020).

The divergence between GDA and SNA does not imply the irrelevance of observable social relations in understanding social structures (Bottero & Crossley, 2011). Instead, it lies in the analytical emphasis on these relationships. In studies employing GDA and field analysis, interpersonal social connections stem from the unequal distribution of various types of capital. These connections are generally not seen—except perhaps marginally—as resources capable of fundamentally altering the power dynamics that structure the field. Essentially, from this perspective, interpersonal relationships alone do not "generate" significant changes in the organization of the analyzed social world (Bottero & Crossley, 2011).

However, the distance and proximity reconstructed through GDA represent a sociological *a posteriori* construction. From a strictly statistical standpoint, these are not comparable across different factorial planes, whereas SNA enables the development of shared tools to measure the form and intensity of structural relationships, thus establishing a robust epistemological framework for producing scientific findings (Wasserman & Faust, 1994). Moreover, GDA projection of "proximity" is not without its own well-known limitations. Statistical tools used to capture the tensions that structure social spaces, such as MCA, often tend to overestimate the "objective" distance between social groups (Cibois, 1997). These groups are assumed to be cohesive based on the pronounced opposition between extreme cases (as pointed out by Cibois). By focusing on oppositions and mechanisms of distinction GDA tend to obscure intermediate situations, which are often the most common situations. For instance, Lahire's (2004) work on cultural dissonance at the individual level reveals that most people develop more plural cultural tastes and practices than the theory of distinction predicts. The social process of distinction frequently hinges on how individuals manage and socially display this plurality of cultural preferences, with certain ways of showcasing that "omnivorousness" is socially advantageous (Coulangeon, 2017). Similarly, artistic workers such as writers attempting to make a living from their craft often have to navigate a range of social subspaces with varying levels of cultural legitimacy because of the low institutionalization of their professional domain (Lahire, 2006). Analyses of their career trajectories demonstrate that they frequently establish connections with local institutions—such as associations, festivals, and reading clubs—that remain invisible when examined solely through GDA.

## 2.3. Toward a cross-fertilization

The irreconcilable nature of these two approaches has long been exaggerated. This debate framing owes much to the logic of distinction within the scientific field itself; for an overview of Bourdieu's evolving relationship with the concept of social capital and the proponents of SNA, see Denord (2020). Since the early 2000s, several proposals have emerged regarding the potential reconciliation of these two methods to better understand the dynamics that drive the formation of social structures.

Some of these mixed approaches are descriptive and involve conducting these two types of analyses in parallel on the same population, demonstrating how the evolution of the structure of the field mirrors the shape that interrelations take between agents (Mach et al., 2011). Others are more integrated, proposing the incorporation of elements from SNA—such as centrality measures, clustering, etc.—into GDA in order to assess their relevance for understanding the structuring of fields (Benz & Bühlmann, 2024; Denord et al., 2011; Eloire, 2011). Finally, some argue that this opposition is largely irrelevant, as a deep analysis of the results from network analysis within a particular social space generally leads to outcomes similar to those anticipated by GDA (Bottero & Crossley, 2011; de Nooy, 2003).

Greene et al. (1989) identify different configurations relating to mix methods in social sciences: rather than ignoring or confronting competing methods, one can adopt approaches that integrate results from various methodologies for "triangulation"—i.e., cross-validation. One can also use a mixed methods framework from a more complementary perspective, which considers the differences between the epistemology behind each methodological framework to develop methods through others (Dietrich-Ragon et al., 2010). Using this typology, it appears that we have moved from a period of relative ignorance, or even opposition, between SNA and GDA to works that mobilize both approaches in a way that confirms and reinforces the results of one through the other by triangulation.

Without pitting them against each other, it seems to us that these two methods offer different perspectives on what they point out about social structures. Integrating their respective limitations into the interpretation of the results yields significant heuristic gains. Therefore, we aim to contribute to forms of articulation that involve the development of SNA results through GDA (and vice versa), as well as the insights that emerge from the cross-examination of the limitations of both methods, leading to a more accurate understanding of the structuring and functioning of spaces for the production and circulation of symbolic goods.

Our work is in line with ecumenical approaches that tend to consider MCA and networks as complementary, especially in the analysis of a network cluster partition, that is at the core of our demonstration. To illustrate how GDA and SNA can be integrated and
mutually cross-fertilize, we propose an analysis of the circulation of French-speaking theatrical productions in Switzerland. The goal is to gain a better understanding of the various principles governing the structuring of diffusion networks in Switzerland, and finally, to map the structure of the work market of ordinary French-speaking actors.

# 3. Data and analytical strategy

## 3.1. Two databases for understanding circulation spaces of French-speaking theatrical productions

The following analyses are based on two data sources. We will begin by introducing these sources and providing an overview of the analyses conducted.

The first dataset (SNA Dataset) was obtained using semi-automated harvesting techniques (web scraping) from the *Archives du spectacle vivant* website.<fnref n="1" /> This collaborative platform systematically compiles programming data from performance venues across a vast majority of Francophone European countries, including Belgium, France, and Switzerland. The collected information includes production titles, performance dates, cast, and the country of production. Initially launched in the early 2000s by a small group of theater enthusiasts, the platform has since expanded considerably, offering extensive coverage of numerous venues and performances since the early 2010s.

For the purposes of this article and our data collection, we consider 'theatrical productions' to be any show that was on the website. Each show has a detailed record on the site, specifying information such as the creative team, (co)producing institutions, tour dates and locations, genre (theater, dance, comedy, music), duration, country of creation, and the data sources used to compile the record. We extracted all records of theatrical productions created between 2009 and 2019 in Switzerland. Although not exhaustive, it provides considerable information on active venues and production in these regions. In this database, we identified 158 Swiss venues that hosted French-speaking Swiss theater productions at least once between 2010 and 2020, accounting for 7944 performances during this period. In our SNA analysis, we define a connection between two venues when they have programmed the same production.

To analyze the structure of this network, we applied the Louvain algorithm, a widely used method for detecting communities in complex graphs (Blondel et al., 2008). This algorithm identifies communities by optimizing modularity, aiming to partition the graph in a way that maximizes the internal density of links within communities relative to the links connecting to nodes outside those communities. In SNA, the density indicator is defined as the ratio of observed links within a group of nodes to the total possible links between them. The Louvain clustering, therefore, provides a partition of subgroups of nodes that exhibit a higher-than-average internal density of connections. Despite certain limitations inherent to the Louvain method—particularly its assumption that a node cannot belong to multiple clusters simultaneously (Traag et al., 2019)—we selected this algorithm over alternatives such as Leiden, Walktrap, or Spinglass. The choice was guided by its optimal balance between clustering quality and ease of interpretation.

The venues and the co-programming network has also been geolocated to provide a more intuitive understanding of the geographical spaces involved in the circulation of French-speaking productions, similar to what is done in the analysis of international scientific collaborations (Maisonobe et al., 2016). Beyond cluster analysis, such plotting strategies are highly useful for interpreting the proximity identified by community detection algorithms and assessing whether proximity based on links aligns with (or diverges from) physical proximity (Glückler & Panitz., 2021).

The second dataset (GDA Dataset) details the characteristics of the identified 158 venues. We developed this database using information sourced from the web, administrative databases, and our own ethnographic expertise. The primary aim was to create a comprehensive landscape of French-speaking Swiss venues for live performances, modeled after the framework established by Picaud (2015) for Parisian music venues. We collected information on how venues are funded: do they rely on private sponsorship or public funding? Do they engage in activities beyond theater programming to generate revenue, such as operating bars/restaurants or renting halls for non-artistic events like congresses or fairs? Our objective was to determine the extent to which venues are situated within different segments of the market for symbolic goods: the 'restricted production' pole or the 'large-scale cultural production' pole (Bourdieu, 1985). In the first case (restricted), cultural goods are "objectively intended for an audience of cultural goods producers" and "tend to develop their own criteria for evaluating their products" (p.17). In the second case (large-scale), the production is aimed at "the general public", subjected to "the laws of competition to capture the largest possible market" (Idem.).

To do so, we gathered data on three main topics: the funding mechanisms of venues, their operational characteristics, and programming (see Table 1).

A first set of variables provides information on the funding sources supporting venues activities (see Table 1, "Economic resources"). This allowed us to determine whether venues rely solely on their economic performance or benefit from the support of external (often public) institutions. These data offer an initial proxy for assessing whether venue activities are driven purely by heteronomous (economic) logic or influenced by other factors. Public funding for the arts is complex in Switzerland. Positioned between nations where the central state plays a significant role in supporting artistic and cultural activities—such as France (Dubois, 1999)— and those where private actors have significant influence—such as Chile (Garreton, 2003)—Switzerland occupies an intermediary position (Perrenoud et al., 2022). Although the federal state has historically limited involvement in the arts domain (Thévenin and Moeschler, 2018), a set of semi-public institutions (Hauser, 2010) or those fulfilling quasi-public service missions have developed nationwide, including distribution companies *Migros* or *Loterie Romande*, both contributing to a significant number of artistic projects

<footnote n="1">¹ See: https://lesarchivesduspectacle.net/</footnote>
<table><caption>**Table 1**
Active variables with absolute (N) and relative (in %) frequencies.</caption><thead><tr><th>Variable types</th><th>Variables</th><th>N</th><th>%</th></tr></thead><tbody><tr><td rowspan="10">Economic resources</td><td>Modalities</td><td></td><td></td></tr><tr><td><em>Funding (multiple choice)</em></td><td></td><td></td></tr><tr><td>Fédération Romande des Arts de la Scène (FRAS)</td><td>47</td><td>29,7</td></tr><tr><td>Loterie romande & Pourcent Migros</td><td>76</td><td>48,4</td></tr><tr><td>Private sponsoring</td><td>100</td><td>63,3</td></tr><tr><td><em>Ticket prices</em></td><td></td><td></td></tr><tr><td>&lt;20</td><td>19</td><td>12,0</td></tr><tr><td>21–30</td><td>47</td><td>29,7</td></tr><tr><td>31–40</td><td>19</td><td>12,0</td></tr><tr><td>41 and +</td><td>43</td><td>27,3</td></tr><tr><td>NR</td><td>30</td><td>19,0</td></tr><tr><td rowspan="10">Venue characteristics</td><td><em>Restaurant</em></td><td></td><td></td></tr><tr><td>Yes</td><td>53</td><td>33,5</td></tr><tr><td>No</td><td>89</td><td>56,3</td></tr><tr><td>NR</td><td>16</td><td>10,2</td></tr><tr><td><em>Creation Year</em></td><td></td><td></td></tr><tr><td>Before 1980</td><td>42</td><td>26,6</td></tr><tr><td>1980–2000</td><td>57</td><td>36,1</td></tr><tr><td>2001–2011</td><td>19</td><td>12,0</td></tr><tr><td>After 2011</td><td>11</td><td>7,0</td></tr><tr><td>NR</td><td>29</td><td>18,3</td></tr><tr><td><em>Halls</em></td><td></td><td></td></tr><tr><td>1</td><td>106</td><td>67,0</td></tr><tr><td>2</td><td>30</td><td>19,0</td></tr><tr><td>3</td><td>11</td><td>7,0</td></tr><tr><td>NR</td><td>11</td><td>7,0</td></tr><tr><td><em>Gauge</em></td><td></td><td></td></tr><tr><td>1–50</td><td>4</td><td>2,5</td></tr><tr><td>51–100</td><td>34</td><td>21,5</td></tr><tr><td>101–150</td><td>23</td><td>14,6</td></tr><tr><td>151–300</td><td>39</td><td>24,7</td></tr><tr><td>301 and +</td><td>39</td><td>24,7</td></tr><tr><td>NR</td><td>19</td><td>12,0</td></tr><tr><td><em>Staff</em></td><td></td><td></td></tr><tr><td>1–3</td><td>13</td><td>8,3</td></tr><tr><td>4–10</td><td>30</td><td>19,0</td></tr><tr><td>11–20</td><td>22</td><td>13,9</td></tr><tr><td>21–40</td><td>18</td><td>11,4</td></tr><tr><td>41 and +</td><td>12</td><td>7,6</td></tr><tr><td>NR</td><td>63</td><td>39,8</td></tr><tr><td rowspan="7">Programming</td><td><em>Function</em></td><td></td><td></td></tr><tr><td>Host</td><td>60</td><td>38,0</td></tr><tr><td>Producer & Host</td><td>86</td><td>54,4</td></tr><tr><td>NR</td><td>12</td><td>7,6</td></tr><tr><td><em>Non-theatrical programming (multiple choice)</em></td><td></td><td></td></tr><tr><td>Comedy</td><td>72</td><td>45,6</td></tr><tr><td>Dance</td><td>79</td><td>50,0</td></tr><tr><td>Music</td><td>108</td><td>68,4</td></tr><tr><td><strong>TOTAL</strong></td><td></td><td><strong>158</strong></td><td><strong>100*</strong></td></tr></tbody></table>

Source: GDA Dataset.

Note: Among the venues, 38 % only host shows without any production activities.

* For multiple choice questions (*Non-theatrical programming* and *Funding*), total percentage is higher than 100.

annually by channeling a portion of their profits (Moeschler, 2009).

Moreover, economic considerations are viewed as legitimate mechanisms for regulating artistic careers, although a substantial number of artists rely heavily on income from these quasi-public institutions or foundations (Bataille et al., 2020). In terms of funding modalities, we sought to determine whether the venues received subsidies from public sources—such as the *Fédération Romande des Arts de la Scène* (FRAS)—or quasi-public entities (including *Pour-cent Migros* and *Loterie Romande*), as well as whether they were supported by one or more businesses. This initial set of indicators signifies the venues’ proximity to quasi-public service institutions or commercial sponsors.

Given that cultural venues are also influenced by profit-making considerations, it is relevant to explore whether they engage in activities beyond theater programming. Among these supplementary activities, running a café or restaurant is particularly common, as it can leverage the regular audience attending performances while generating revenue on non-performance days. Furthermore, the literature on the economics of live arts has long highlighted that support from public or semi-public institutions is essential for maintaining low pricing policies (Baumol & Bowen, 1968). Therefore, pricing policies serve as another meaningful indicator of the
extent to which profit-oriented logic governs venue management.

A second set of variables provides information about non-economic characteristics of the venues (see Table 1, “Venues characteristics”). The politico-historical context also profoundly influences the extent of public institutional support for cultural productions, thereby shaping how reliant venue management must be on market-oriented (i.e. heteronomous) practices (Dubois, 1999; DiMaggio & Stenberg, 1985). From a path dependency perspective, one could hypothesize that the development of cultural institutions remains strongly shaped by the cultural policy trends that underpinned their establishment. The period before 1980 was marked by the near absence of structured cultural policies at the federal level (Clottu, 1975). By contrast, 1980–2000 witnessed the emergence of a more robust institutional framework, bolstered in part by public policies (Moeschler, 2011). The period from 2000 to 2011 is characterized by Switzerland’s commitment to investing in culture and sciences to enhance its international standing (Hauser, 2010). In 2011, a significant reform of the Swiss comedian employment scheme was implemented (ROSA, 2011). Consequently, the year was identified as a landmark in the contemporary history of Swiss theater.

Since 2011, the performing arts sector in Switzerland has undergone significant transformations, characterized by professionalization and a steady increase in active participants. Between 2011 and 2019, Structural Business Statistics (STATENT) recorded an increase in jobs within theater and ballet troupes from 756 to 1213, representing a 60 % growth (Rota, 2022). Despite certain methodological limitations that may underestimate the actual number of individuals working in the performing arts, this growth has underscored systemic challenges. These challenges include limited infrastructure, constrained funding opportunities, and heightened competition for audiences, leading to what some describe as potential overheating of the sector.

In response to these pressures, new discussions have emerged around rethinking support mechanisms for the performing arts. Stakeholders are advocating for a more comprehensive approach that encompasses other stages of the production cycle. Support should be extended over a longer period and include various aspects such as artistic research, fundraising, more frequent deadlines for applications, reconsideration of rehearsal times, extension of production lifespans, enhanced support for dissemination, and the creation of mechanisms to aid in the revival of productions. Additionally, there is a growing movement towards harmonizing public cultural policies across linguistic and cantonal boundaries, reflecting a broader recognition of the need for coordinated action to address geographic and institutional disparities within the Swiss performing arts landscape. Regarding these historical landmarks, we identify four periods of creation: “Before 1980,” “1980-2000,” “2001-2011,” and “After 2011.”

We also collected data on venue size (number of halls and seating capacity of the largest hall) and human resources (including the number of employees). This information helps to understand the constraints influencing venue management as well as their ambitions regarding audience reach. Are they aiming for the largest possible audience, requiring large halls and numerous employees to manage them? Or are they, conversely, part of the subfield of “restricted cultural production” (Bourdieu, 1985), targeting primarily to cultural producers and highly cultured theatergoers?

Finally, we incorporate specific indicators to characterize venue programming (see Table 1, “Programming”). First of all, the choice to schedule shows created within the venue itself (“Producer & Host”), or conversely, to only program shows created elsewhere (“Host”), seemed to us a relevant initial indicator for distinguishing between venues located at the creative/autonomous pole or not. Then, the inclusion of comedy performances is particularly relevant, given the unique status of this genre (Friedman, 2015). Comedy seems to be an unintellectual genre in the cultural hierarchy of shows, although it is also popular, drawing a large audience. From our perspective, programming comedy and stand-up can thus be seen as indicators of how far venues tends to be located at the “large-scale” pole rather than the “restricted production” pole. Additionally, the programming of dance and music (excluding classical music and opera) has emerged as a key factor in assessing the positioning of venues within the live-performance diffusion landscape. It is important to recognize that not all artistic offerings carry the same level of legitimacy—particularly music-only events, which in our case primarily include “pop”, “rock” and more popular forms of “jazz”. The positioning of venues with respect to dance programming is more complex to characterize. However, it should be noted that ballet and performances by large dance companies require extensive stages and specific infrastructure, which tend to elevate production costs.

We chose the variables presented in Table 1 because they provide insights into the legitimacy of the venues studied. These variables show which venues are the most recognized and most autonomous in relation to temporal and economic imperatives; these venues are publicly subsidized.

In terms of funding, private sponsorship emerges as the most common source, utilized by 63.3 % of venues. Loterie Romande & Pourcent Migros follows with 48.4 %, while FRAS funding supports only 29.7 % of venues. Ticket pricing is relatively evenly distributed, with the 21–30 CHF range being the most prevalent (29.7 %). High-price tickets (41+ CHF) account for 27.3 %, and the least expensive tickets (under 20 CHF) make up 12.0 %. Additionally, about a third of venues (33.5 %) operate a restaurant, reflecting an additional source of revenue or service offered alongside their cultural activities.

The data also reveals trends in the creation year of venues. Most were established between 1980 and 2000 (36.1 %), while older venues, created before 1980, make up 26.6 %. More recent venues, established after 2001, are less common, with only 12.0 % created between 2001 and 2011, and 7.0 % after 2011. When considering the number of halls, the majority of venues (67.0 %) have just one hall, with fewer venues having two halls (19.0 %) or three or more (7.0 %). Seating capacity varies widely, but venues with 151–300 seats and those with 301+ seats are the most common, each comprising 24.7 % of the sample. Smaller venues with seating capacities of 1–50 are rare, representing only 2.5 % of the total. Staffing levels indicate that most venues employ small teams, with 27.3 % having between 1 and 10 staff members. Larger venues with 41 or more employees are uncommon, comprising only 7.6 %.

Programming choices show that a majority of venues (54.4 %) engage in both hosting and production activities, while 38.0 % operate solely as hosts. Music is the most commonly featured non-theatrical genre, with 68.4 % of venues offering music-related events. Dance is also a significant part of programming, present in 50.0 % of venues, followed by comedy (45.6 %).

In summary, our sample of venues offers a diversified representation of the theater venues landscape, encompassing spaces that
blend indicators of heteronomy—such as private sponsorship, larger seating capacities, and additional revenue-generating activities—with characteristics more commonly associated with the restricted or autonomous production pole, including smaller venues, modest ticket prices, and specialized programming aimed at culturally engaged audiences. To assess the extent to which the circulation space of French-speaking Swiss theater productions is shaped by this polarization scheme, we conducted a MCA using all 9 variables and their 31 modalities. We exclude non-responses (NR) from our analyses.

## 3.2. Beyond the factorial plane

Building on our case, one of our ambitions was to move beyond conducting separate analyses (SNA on one side, GDA on the other) and instead explore strategies that promote cross-fertilization between the two approaches.

In most studies combining SNA and GDA (see, for example, Benz & Rossier, 2022; Éloire, 2011), the analytical strategy involves introducing network variables (centrality, intermediacy, etc.) into MCA as active or illustrative variables—i.e. projecting information about individuals' positions in the network structure onto the factorial plane. Our approach aimed to maintain parallelism in the analysis by starting with network analysis and then using the results of MCA as keys to interpret the structure of the network. Essentially, the goal was not merely to use the results of the network analysis to confirm and reinforce MCA findings, but rather to explore ways to foster a dialogue that acknowledges the characteristics and analytical strengths of both methodologies.

The cross-utilization of both methods aims to leverage individual strengths. Through GDA and MCA, the objective is to distill and synthesize, across various identified dimensions, the key tensions that objectively structure the distribution space for French-speaking theatrical productions in Switzerland. Through SNA, the goal is to map the concrete organization of distribution networks based on a shared criterion: the co-programming of the same productions.

This led us to consider the projection of MCA results beyond their use in constructing a factorial plane—such as through box-plots—and to treat them with statistical tools other than those traditionally mobilized in GDA, such as analysis of variance (ANOVA) and the post-hoc Tukey test. This type of crossroads between methods primarily designed for continuous variable analysis (ANOVA, linear regressions, etc.) and methods mainly devised for categorical variable analysis (MCA) is still relatively rare, especially in so-ciology, where methodological divisions are potent, and often conceived as grounded in theoretical distinctions.

To sum up, first, the co-programming network structure was analyzed using various tools (network spatialization and cluster detection). Second, polarizations within our population was analyzed based on the results of MCA conducted on the variables presented above. Finally, the dispersion of venues within the different clusters were examined identified in the network concerning the coordinates of the first two dimensions of MCA. Our argument here is that using the coordinates of points obtained through MCA in treatments other than projecting points onto a factorial plane, such as ANOVA and post-hoc Tukey tests, is a way to consider the implications of MCA results beyond the factorial plane. Accordingly, the information synthesized through various dimensions of MCA enables the construction of a heuristic and relatively intuitive interpretive framework for clustering partitions within the co-programming network. In turn, this cross-analysis also highlights a limitation of GDA: its tendency to capture the social space of venues primarily through its most pronounced “objective” polarities, potentially underestimating the influence of less distinct sub-spaces. As discussed below, we assume that these subspaces hold nuanced positions on the legitimacy scale and are, in our view, characteristic of certain modes of “ordinary” artistic work.

All analyses were conducted using R and Rstudio software, specifically employing the igraph (Csardi & Nepusz, 2006), Factominer (Lè, Josse, & Husson, 2008), and rstatix (Alboukadel, 2019) packages for statistical analyses and ggplot2 (Wickham, 2016) package for visualization. In conclusion, we revisit the implications of being able to process these data using a single software and unified syntax.

# 4. Results

## 4.1. A clustered co-programming network

From the SNA dataset, we reconstruct the co-programming network of venues that hosted French-speaking Swiss productions during 2010–2020 (Fig. 1.A). Each point represents a venue and each link indicates common programming during the specified period. The thickness of the links represents the frequency of these co-programings. Fig. 1.B represents the location of venues based on cluster membership (Louvain).

Here, we observe that the co-programming network is particularly dense in venues in French-speaking areas. Links with and between venues located in the German- and Italian-speaking regions of Switzerland are less common. Overall, venues showcasing Francophone Swiss production are concentrated in French-speaking Switzerland (green). A small proportion of the production manages to cross the French-speaking area border and is programmed in venues in German-speaking (in red) or Italian-speaking regions (in blue). This reflects a well-known characteristic of the geography of the arts in Switzerland: Swiss artistic productions seldom circulate across the entire territory and generally remain associated with the linguistic sphere in which they are initially rooted (Jost, 1985), resonating more in countries with a shared language and culture (France, Germany, and Italy) than at the scale of the Swiss Confederation (Gamboni et al., 1987). The specificity of the region north of Lake Geneva in French-speaking artistic work geography is also evident here: despite a relatively dense network of venues throughout the French-speaking territory, a significant concentration of structures is found along the north cost of Lake Geneva, making it the true heart of performing arts in French-speaking Switzerland.

The Louvain community detection algorithm led to the partitioning of venues that partially reflect this observation. Clusters 1, 2, 3, and 5 are mainly located in western Switzerland, whereas Cluster 4 consists of venues situated in eastern German-speaking cantons.
<figure><img src="image_5.png" /><figcaption>B. Clusters localisation</figcaption></figure>

<figure><img src="image_6.png" /></figure>

**Fig. 1.** Co-Programming Networks Among Venues Hosting French-speaking Swiss Productions (2010–2020).

Source: SNA Dataset.

Note: Almost all of the venues belonging to Cluster 1 (red) are located in the French-speaking regions of Switzerland.
However, even with the projection of a network onto a map, it is challenging to elucidate the principles that organize the partition detected using the Louvain algorithm. We can assert that Cluster 5 comprises venues that are relatively peripheral or at least weakly connected to the main spaces for the diffusion of Francophone Swiss productions. To understand what distinguishes Clusters 1, 2, and 3 the results from MCA are highly useful.

## 4.2. A bidimensional space

Subsequently, we conducted MCA based on the 9 variables in our GDA dataset (see Table 1). We focused on the first two dimensions of MCA, which accounted for 72.1 % of the expressed variance (49.8 % and 22.3 % for the first and second dimensions, respectively).<fnref n="2" /> Beyond the second dimension, the variance expressed by each axis showed a significant decrease, prompting us not to incorporate other dimensions in the analysis presented here.<fnref n="3" /> Fig. 2 shows the modalities that contribute more than the average (2.63) to the cloud variance in the factorial plane formed by the intersection of dimensions 1 and 2.

The first axis, represented horizontally, primarily contrasts the venues based on their size and age. The modalities related to the number of halls, employees, capacity of the largest hall, and ticket prices are the most influential. On the left side of the plan are large structures employing >41 people, with at least three halls dedicated to public performance, with the capacity of the largest halls exceeding 300 seats. In these big venues, there is often a restaurant that is open even on days without performances, indicating the need for economic activity beyond artistic endeavors. These venues tend to have the highest prices, with tickets costing more than CHF 41 (approximately USD 47). On the right side of the axis are venues with modest capacities (51–100 seats). The first axis also contrasts structures based on funding sources. The "smaller" structures on the right side of the axis are less likely to benefit from sponsorship by private companies, while the "larger" structures are more likely to receive private and public funding (such as FRAS). Finally, the first axis differentiates venues based on their creation date and propensity to schedule dance performances. The "larger" venues tend to be older, suggesting that size partly reflects the longevity of the objectified cultural capital these venues accumulate and embody. For example, historic city center theaters in major Swiss cities, both French- and German-speaking, founded in the first half of the 19th century during the first wave of professionalization of dramatic activities (Schläpfer, 2001), and especially on the French-speaking side, venues founded in the fervor of the 1960s–1970s (Sutermeister, 2000). The contrast regarding the (non)programming of dance performances can be interpreted as a ripple effect of the opposition regarding the size and hosting capacities of venues; a significant portion of dance performances requires a large stage for dancers’ movements, especially ballet.

The second axis, represented vertically, compares venues based on programming and proximity to the most legitimate theatrical practices. Direct involvement in the production of shows, or solely serving as hosts, is a significant distinguishing criterion. The decision to schedule comedies or musical performances is a differentiating factor. The creation date and receipt of funding from FRAS are also decisive. At the top of the plan are venues both host and produce shows, never program comedies (stand-up or comic plays) or musical performances and receive funding from public institutions. At the bottom of the plan are venues dedicated solely to hosting and with recent creation dates (2001–2011), equipped with large hall (capable of accommodating over 300 people) and a substantial number of employees (21–40). The second axis seems to contrast venues located in the most autonomous pole of the French-speaking theatrical space, encompassing some *avant-garde* theaters and venues that are more focused on the dissemination of more mainstream theatrical forms and are more market-oriented (Bourdieu, 1992).

In studies that rely on GDA, the analysis of factorial maps and the weight of different active variables in polarizing the axes constitute the central point of the demonstration. Illustrative variables can then be introduced to complement our understanding of the reconstructed social space. However, they rarely go beyond this stage of representing MCA results in the form of a factorial map. By using the coordinates of venues in the first two dimensions of MCA, one can rely on the modeling results to elucidate other dimensions of analysis, such as the structure of their co-programming links.

## 4.3. Reading the network structure through MCA coordinates

Fig. 3 shows the intra-cluster dispersion in relation to the coordinates on axes 1 (A) and 2 (B) of MCA. To test the significance of inter-cluster differences from this perspective, we used a classic ANOVA test and a post-hoc Tukey test. The results of the post-hoc analysis are indicated above the boxes by stars (0.1 > *p* > 0.5=*, 0.5 > *p* > 0.01=**, 0.01 > *p* =****) only for pairs in which the difference is significant at the 0.1 threshold.

The first dimension of MCA is crucial for explaining the cluster partition of circulation networks between venues. Clusters 1 and 2 significantly differ from Clusters 3 and 4 in terms of their position on the first axis. Clusters 1 and 2 seem to include mainly small venues (their coordinates are generally >0 on the first axis), while Clusters 3 and 4 consist of medium to large venues (their coordinates are generally <0 on the first axis). Therefore, it appears that the diffusion networks are primarily segmented based on the venues’ capacity, certain productions requiring such infrastructure (as is the case with dance ballets, for example) that it is impossible to schedule them in venues that are too small. Furthermore, audience capacity seems to be fundamental in explaining this initial opposition between diffusion networks. The different co-programming clusters differentiate themselves less systematically regarding the venue coordinates on the second dimension of MCA. The main opposition here is between Clusters 2 and 3. The venues in Cluster 2 are those that are positioned highest on the axis of cultural legitimacy, while Cluster 3 seems to group venues more anchored in the

<footnote n="2">² To obtain the variance contribution of each dimension, see the Supplementary Material (Figure 4).</footnote>

<footnote n="3">³ For an overview of the distribution of each variable and modalities to the two dimensions intertia, see the supplementary material (Figure 5).</footnote>
<figure><img src="image_7.png" /><figcaption>**Fig. 2.** Modalities with Above-Average Contribution to Variance in the MCA Factorial Plane (Dimension 1 and 2).</figcaption></figure>

Source: GDA Dataset.

Note: The modalities of the variables related to programming (blue) are primarily distributed along Axis 2.

heteronomous pole, a priori more market-oriented. This analysis confirms that Cluster 5, which seems to have no distinct traits regarding the post-hoc test results, regroup mainly peripheral structures, that have nothing in common except that they are not included in the main theatrical professional worlds.

Examining the situation of Clusters 3 and 4 in this context is particularly insightful. These two circulation subspaces are not distinguished by a particular anchoring on either side on the second axis. However, the morphology of the boxplots for these two clusters is interesting. The Cluster 4 boxplot is very long, indicating a high dispersion of venues associated with it along the axis. These venues, mostly outside French-speaking Switzerland, seem to be primarily connected by their geographical location in German-speaking cantons. This is because they appear to constitute a network linking Geneva to eastern Switzerland, which they find coherent and less in terms of their relative position regarding our indicator of cultural legitimacy. The size of Cluster 1 boxplot is smaller than that of Cluster 4, with a median of approximately 0. Within this cluster, dispersion is lower, and venues are concentrated around an average position. Cluster 1 is mainly located in French-speaking Switzerland, similar to Clusters 2 and 3. Its main characteristic is its average position on the legitimacy scale.

In summary, a first circulation space emerges, encompassing venues of significant size with several decades of existence and is located on either side of the Swiss linguistic-cultural border (Cluster 4). The three other main circulation spaces detected through the Louvain algorithm (Clusters 1, 2, and 3) are more centered in French-speaking Switzerland. They also differ in terms of age and size, but more specifically in terms of legitimacy. Clusters 2 and 3 constitute two circulation spaces in the same geographical area, distinguished by proximity to the *avant-garde* theater pole (Cluster 2) and distance from the most legitimate forms of theater (Cluster 3). The last circulation space (Cluster 1), mainly located in French-speaking Switzerland, appears to occupy an intermediate position on the cultural legitimacy axis.

# 5. Discussion/conclusion

This study demonstrates how the cross-use of network analysis and geometric data analysis deepens our understanding how circulation of symbolic goods is structured. The analysis is based on the circulation of French-speaking Swiss theatrical productions in contemporary Switzerland. Although mapping the co-programming network provides an interesting basis for understanding circulation spaces, we observed that the use of cluster detection algorithms leads to a partition that is difficult to interpret. Leveraging GDA
<figure><img src="image_8.png" /><figcaption>**Fig. 3.** Intra-clusters Coordinates Dispersion (Dimension 1 and 2).</figcaption></figure>

Source: GDA & SNA Datasets.

Note: The coordinates of the venues on Dimension 2 mainly distinguish the venues of Cluster 2 (yellow) and Cluster 3 (green)

sharply illuminates this partition by distinguishing two axes of differentiation among the clusters: age and size on one hand and legitimacy and proximity/distance to the *avant-garde* theater pole on the other. This provided key insights for easy comprehension of network partitioning. With regard to the implications of our result regarding the specific situation of “ordinary” artists, we propose some opening reflections on the mixed approach on “mapping social space” in this paper.

## 5.1. Mapping the unseen world of ordinary artists

From a professional perspective, the career space of "ordinary artists," i.e. artistic workers who are neither rich nor famous, living or trying to live off their art (Perrenoud & Bois, 2017), is polarized around two ideal types: that of artisans, primarily involved in the least legitimate tasks of the profession, confined to activities reproducing existing aesthetic forms on the one hand; that of the creators on the other, recognized for individuality and originality of their works, more in line with the canons of the legitimate artist that has emerged in Western societies, starting from the 19th century (Perrenoud, 2007). The primary inscription to one pole or the other
partially depends on individual resources (especially cultural capital), but also on the structure of job opportunities in a given territory (Perrenoud & Bataille, 2017).

Here, one can hypothesize that Cluster 2 constitutes primarily the space of circulation for "creators" comedians, while Cluster 3 is more for "artisan" comedians. However, a lasting inscription in either of these two poles remains precarious, especially concerning the "artist" pole where positions are limited and highly competitive, especially in the context of potential overheating (Rota, 2022). Therefore, positions of waiting develop in parallel to—or between—these two poles, less marked by the seal of legitimacy than those located at the "artist" pole, but allowing to stay in the professional game by ensuring some work. In these spaces, ordinary artists with contradictory profiles and ambitions are likely to intersect, find resources to coordinate, and ensure that the work is completed despite potential contradictions. It is in this space of "entertainment"—between pure "animation" and pure "creation" (Perrenoud, 2006)—that we can identify the diffusion circuit of Cluster 1.

Our analysis demonstrates that the structure of French-speaking live performance productions operates through mechanisms similar to those Bourdieu (1992) described in *The Rules of Art* for the literary field. A chiastic structure emerges with a restricted production pole—the “artist” pole—, characterized by smaller venues receiving greater public funding, in contrast to a commercial pole—the “artisan” pole. This framework provides several insights. The intermediate space represented by Cluster 1 is a particularly original finding. All agents precisely don’t fit neatly into either the *avant-garde* or commercial poles. Some operate within an inter- mediate space that connects the two poles, bringing together creators and artisans. We may hypothesize that this “entertainment” network provides creators with opportunities to compensate for gaps in work within the creative pole, while offering artisans a space for symbolic valorization. The distinction between Clusters 1, 2, and 3 made possible by the cross-analysis mobilizing SNA and GDA is imperative to elucidate the specific mechanisms that polarize the activities of ordinary performing arts workers in most contemporary industrialized societies (Faulkner & Becker, 2009).

## 5.2. Toward more ecumenical analytical strategies

The articulation between SNA and MCA to better map the structure of cultural fields raises two remarks regarding its conditions of possibility.

First, in his analysis of the diffusion process of sequence analysis tools in social sciences, Robette (2016) distinguishes different moments in the dissemination of this particular methodology in the international sociological community. Initially, after the publi- cation of seminal articles, there is a period of methodological "proselytism," followed by a period of "secularization." The use of religious vocabulary is not accidental here. The competing promotions of different methodologies can resemble chapel wars among supporters, which are especially intense, as competition is intensified by the dominance of certain methodological orientations over others, as regression analysis in contemporary North American sociology (Ollion, 2011). The relative ignorance in which SNA, GDA, or regression analysis still develop today leads us to believe that "proselytism" does not entirely fade away with the broader diffusion of methodological tools and their stabilization. Moreover, practices related to methodological ecumenism remain relatively rare, but are developing, as evidenced by this special issue. Our sense is that this shift from proselytism toward more ecumenism is well underway today, given the generational renewal of academic sociologists and the development of widely accessible training support (online tutorials, detailed manuals, and summer schools).

Second, overcoming methodological divides is linked to the development of tools that concretely facilitate their integra- tion—notably R software and its multiple packages. From a practical standpoint, implementation of the various methodologies employed here requires proficiency in different software programs, each operating in its own programming language. For example, regression analysis specialists were traditionally trained on SPSS, STATA, or Matlab offering a choice between Pajek, NetDraw, or UCINET, whereas the SPAD software contained all the specific tools for geometric data analysis. Additionally, because most of these software programs are proprietary, individuals who want to use them have to acquire licenses, sometimes at a relatively high cost. In practice, in terms of both practicality and material resources, establishing analysis frameworks that connect network, factor, and regression analyses remains costly.

This methodological segmentation imposed by software is now widely challenged by the development of R and its unique syntax (C++), open source and cross-platform, the popularity of which has surged among academics since the early 2000s (Muenchen, 2012). Owing to its extensive user community, R continues to incorporate an increasing number of features/packages (Staples, 2023). This development, coupled with the widespread use of user-friendly interfaces such as RStudio, allows for the integration of results, al- gorithms, and visualizations specific to each of the aforementioned methodologies by mobilizing different packages and their relative functions within a single script. This significantly contributes to facilitating opportunities for dialogue, integration, and supporting more ecumenical approaches on the methodological front, which is the primary goal of this study.

## Notes on contributors

Pierre Bataille is Maître de Conférences (Assistant professor) at the Université Grenoble Alpes, conducting research on inequalities in artistic and academic careers in a comparative perspective.

Marc Perrenoud is Maître d'enseignement et de recherche (senior lecturer) in sociology of work at the Université de Lausanne and conducts research on musical work and artistic consecration.

Robin Casse holds a Ph.D in sociology from the Université de Lausanne. He is currently chargé d'études at the Université Grenoble- Alpes and conducts research into the stratification of educational and career paths in the field of performance arts engineering.

Carole Christe has just completed her Ph.D. in the sociology of artistic and cultural work at the Université de Lausanne. She worked
on the processes of consecration and programming in the fields of contemporary dance and theater in French-speaking Switzerland, for which she conducted a five years ethnography.

Mathias Rota is a researcher at the University of Applied Sciences and Arts of Western Switzerland (HES-SO). He conducts studies on the art worlds.

## Disclosure statement

No potential conflict of interest was reported by the authors.

## CRediT authorship contribution statement

**Pierre Bataille:** Writing – original draft, Visualization, Methodology, Formal analysis, Data curation. **Marc Perrenoud:** Writing – original draft, Methodology, Funding acquisition, Formal analysis, Data curation. **Robin Casse:** Writing – original draft, Methodology, Investigation, Formal analysis, Data curation. **Carole Christe:** Writing – original draft, Methodology, Formal analysis, Data curation. **Mathias Rota:** Writing – original draft, Visualization, Formal analysis, Data curation.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j-poetic.2025.101999.

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