dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments. Warm thanks to the  Q-BEx Consortium  for contributing to the Delphi survey (twice!), and to the workshop participants for their insights and enthusiasm. We are grateful to  Bissera Ivanova  for helping us communicate anonymously with the panellists. We thank the reviewers for inviting us to go deeper into the discussion and to clarify the remit of our enterprise. This project is funded by the  Economic and Social Research Council  (grant reference:  ES/S010998/1 ), which is gratefully acknowledged.
This article introduces data collected in the Citizens' Attitudes Under Covid-19 Project (CAUCP), which surveyed public opinion throughout the Covid-19 pandemic in 11 democracies between March and December 2020. In this paper, we present a unique cross-country panel survey of citizens' attitudes and behaviors during a worldwide unprecedented health, governance, and economic crisis. This dataset investigates the behavioral and attitudinal consequences of multifaceted Covid19 crisis across time and contexts. In this paper, we describe the design of the CAUCP and the descriptive features of the dataset; we also present promising research prospects.
Background & Summary This article introduces data collected in the Citizens' Attitudes Under Covid-19 Project (CAUCP), which surveyed public opinion throughout the Covid-19 pandemic from March to December 2020. In this paper, we present the dataset collected in 11 advanced democracies, which is deposited in open access on the Sciences Po Dataverse. It constitutes a unique cross-country panel survey of citizens' attitudes and behaviors during a worldwide unprecedented health, governance, and economic crisis (N = 27,100 unique respondents over four waves). Since the Covid-19 crisis tapped into all social dimensions, or crisis characteristics, it affected most peoples' lives, and generated unprecedented individual and collective challenges to the public's health, the economy, and social life  1.
For instance, available cross-country surveys are mostly cross-sectional. Thus, they overlook the evolution of public opinion, and the durability of the effect, throughout a (at least) two year-long eventful crisis  11. Further, cross-sectional studies cannot establish causal mechanisms on the determinants of public attitude formation and change. On the other hand, existing panel studies are often limited to a single country, falling short of capturing important contextual effects on political behavior  12  (e. g. in Austria  13  or the Netherlands  14  ). Some studies do combine cross-country comparisons with panel designs through opt-in questions added in already existing panel surveys-although necessarily limiting the breadth of investigation  15. The CAUCP addresses these issues by providing public opinion panel data from 11 advanced democracies over the year 2020 to examine the longitudinal and cross-country dynamics of citizens' preferences, perceptions, and behavior.
Survey design. The CAUCP panel data was collected (Computer-Assisted Web Interview) in four waves, from the outset of the pandemic (Wave 1 in late March 2020) and throughout 2020 (Wave 2 in April 2020, Wave 3 in June 2020, and Wave 4 in December 2020). Therefore, the first wave of the panel covers the implementation of the first health restrictions in mid-March in Europe. The data collection covered the evolution of the pandemic over the summer 2020 (lower intensity of the pandemic and loosened restrictions in the Northern hemisphere vs. higher intensity of pandemic and more stringent policies in the Southern hemisphere), and it extended to December 2020 (as the pandemic dynamic reverses again between South and North). Figure  1a  shows the temporality of the waves of the CAUCP panel together with indicators on the strength of the pandemic (number of new cases and covid-related deaths  16  ) and on the stringency of governments' response to the pandemic (Oxford Covid-19 Government Response Tracker  17  ).
Ethical validation. The CAUCP data collection has been approved by the Toulouse School of Economics - Institute for Advanced Studies in Toulouse (TSE-IAST) Review Board for ethical Standards in Research in April 2020. The collection of the CAUCP dataset complies with all ethical regulations of public opinion survey data. Participants have been informed of the purpose of the study and consented to sharing their data. Individual data has been entirely anonymized. A similar process is ongoing at Sciences Po to provide the overall ethical approval. Respondents. CAUCP surveyed of total of 27,100 uniquely identified respondents, which constitutes 53,083 observations across the four panel waves. In order to increase the representativeness of the samples, each panel wave includes a minimum of 1,000 respondents in eight countries and about 2,000 in France, Germany, and the USA.
Data records The data generated by the CAUCP project is available in open access on the Sciences Po Dataverse  18. We have uploaded sub-datasets for each wave in each country of the study in TAB format. The country*wave sub-datasets have been cleaned to standardized variable names across country and wave sub-datasets datasets. We have also included detailed codebooks for each for each sub-dataset which describes all the variables included in each sub-dataset (variables labels, answer categories, answer labels, country specific   In addition to the individual country*wave files and documentations uploaded on the institutional repository of Sciences Po, we have uploaded a merged dataset on figshare repository  19. This merged dataset includes the observations for the eleven countries and the 4 waves, as well as an extended codebook in XLSX format, detailing variable types, names, labels, values, value labels, and inclusion or not in each panel wave (this codebook includes generic question wordings, as well as separate tabs for each country which details country-specific questions and answer categories).
Respondents of the CAUCP panel data were selected through quota sampling, which were based on a combination of multiple socio-demographic characteristics. In the 11 countries of the panel, sampling quotas were based on gender, age, occupation, region of residence, type of environment (town size or population density). In some countries, quota samplings also include additional weighting characteristics, such as ethnicity in the USA, or education in France. The full structure of unweighted samples, weighting coefficients and targeted populations for each country and each wave is presented in Appendix A. In each survey, weighting scores were obtained thanks to RIM weighting (Random Iterative Method-'Raking'). Identical questionnaires were administered in all countries for each wave of the CAUCP survey-albeit some questions were adapted to country-specific characteristics (notably with regards to ideology, and political and Fig.
The CAUCP consists of 317 unique variables measured in all countries (some variables were introduced or drop in different waves). Table  2  presents a selection of the most relevant topics and variables covered in CAUCP data, grouped by main research themes. In addition to the variables presented in Table  2 , the CAUCP survey includes extensive information on respondents' socio-demographic characteristics (gender, age, religiosity, income, education, household description, employment status and trajectory). In this overview, the variables related to a series of randomized experiments carried simultaneously to the CAUCP fieldwork are excluded. Such experiments addressed RQ1 (Behavioral and attitudinal reaction to Covid-19 related policies) and focused on individual compliance to health regulations-data and results are presented separately elsewhere  20.
Usage Notes To conclude the presentation of the CAUCP dataset, we present three key dimensions covered by our survey: policy compliance, attitudinal dynamics, and democratic accountability. We describe three key variables to study the possibly large and lasting effects of the Covid-19 crisis on social and political life. Public health policy compliance. Compliance with Covid-19 related policies is both a salient political debate and constitutes a promising research agenda. Indeed, the preventive and sometimes restrictive policies implemented during the Covid-19 pandemic have been extensively discussed in the public debate. We identify two dimensions of policy compliance: individual behavior (i. e. respecting restrictive regulations) and acceptance/ evaluation of Covid-19 related measures (i.
The CAUCP data confirms that citizens' policy response is complex and context dependent. Looking at the satisfaction with the government's handling of the Covid19 crisis, we observe important time and country variation (Fig. 4 ). Indeed, in the different countries, the level of satisfaction is extremely high (Australia, New Zealand, Austria), average (France, Italy, USA), or generally low (Brazil, Poland). Additionally, trends of satisfaction are either increasing (Australia), stable (France, New Zealand), or declining (Sweden, United Kingdom). In addition to attitudes toward the government, social science research should further investigate the electoral consequences of the crisis. Indeed, local sanitary contexts and corresponding health policies have affected turnout rates in several European local elections, increasing turnout in some cases  33  or depressing it in others  34, 35.
of its scale (4 waves, 11 countries) and the constraints of the Covid-19 pandemic, the CAUCP surveys required a resolutely collective research endeavor. The dataset on Citizens' Attitudes Under Covid19 Project (CAUCP) was developed by Sylvain Brouard and Martial Foucault at the CEVIPOF in Sciences Po (France), in close cooperation with multiple research partners and institutional support. The data collection has been piloted by a steering committee also including Michael Becher (IAST Toulouse and IE University in Madrid) and Pavlos Vasilopoulos (University of York).
Acknowledgements The local implementation of surveys in individual countries has associated scholars in all the countries of the study:  Christoph Hönnige  ( University of Hannover );  Kevin Arceneaux  ( Temple University );  Eric Bélanger  ( McGill University );  Jean-François Daoust  ( University of Edinburgh ),  Vincent Pons  ( Harvard Business School and NBER );  Ruth Dassonneville ,  Erik Lachapelle ,  Richard Nadeau  ( University of Montreal );  Vincenzo Galasso  ( Bocconi University );  Hanspeter Kriesi  ( European University Institute );  Grégoire Rota-Graziosi  ( University of Auvergne );  Sandra León  ( University Carlos III );  Dominique Reynié  ( Sciences Po );  Daniel Stegmueller  ( Duke University ). Throughout the data collection, the  CAUCP  project has received financial support from the following institutional partners:  Agence Nationale de la Recherche  (Grant  ANR-20-COVI-0079 ),  French Agency for Development (AFD) ,  World Bank ,  CEVIPOF, France Stratégie, Fondapol, IPSOS -Sopra Steria, Policy Center  for the New South,  Région Nouvelle-Aquitaine, Région Occitanie, EUI ,  IAST  funding from  ANR  under the Investments for the  Future ("Investissements d'Avenir") program , Grant  ANR-17-EURE-0010 ,  Unicredit Foundation, University of Hanover, CERDI (CNRS) , and  IE University.
Study design. Because of its scale (4 waves, 11 countries) and the constraints of the Covid-19 pandemic, the CAUCP surveys required a resolutely collective research endeavor. The dataset on Citizens' Attitudes Under Covid19 Project (CAUCP) was developed by Sylvain Brouard and Martial Foucault at the CEVIPOF in Sciences Po (France), in close cooperation with multiple research partners and institutional support. The data collection has been piloted by a steering committee also including Michael Becher (IAST Toulouse and IE University in Madrid) and Pavlos Vasilopoulos (University of York).
Remerciements Les auteurs remercient chaleureusement pour leur accueil et l'aide constante qu'ils leur ont apportée, pendant la mission et dans la préparation de celle-ci, la Dott. ssaClaudia  Montuschi, directrice du Dipartimento dei manoscritti de la Biblioteca Apostolica Vaticana ; la Dott. ssaÁngela  Núñez Gaitán , directrice du Laboratorio di conservazione e restauro; il Dott. Andrea Pedditzi ,  direttore della Biblioteca Statale del Monumento Nazionale di Grottaferrata; la Dott. ssaAnna Onesti, conservatrice de la Biblioteca Statale del Monumento Nazionale di Grottaferrata ; le  Dott. Massimo Breazzano ,  responsable du Laboratorio di restauro di Grottaferrata.
Data and estimation 3. 1. Data 3. 1. 1. Individual-level data and outcome variables I use four waves of microdata from the nationally representative Zambia Demographic and Health Surveys (DHS) conducted in  1996, 2001, 2007 and 2013. Appendix C provides a description of the sampling frame. Within sampled households, all women aged 15-49 who were either permanent residents of the household or visitors present on the night before the survey were eligible for survey interview. The DHS collect data on birth history, 3  with detailed information on delivery conditions for births that occurred during the last five years preceding the survey, as well as maternal and under-five health, including anthropometric measurements and child death history. Place of birth and the presence of a skilled birth attendant during childbirth constitute our main indicators of delivery conditions.
Health facility census I complement the DHS with facility-level data obtained from the national Zambian Health Facility Census conducted in 2005. Precise information on the geographic coordinates, physical infrastructures, equipment, services offered and head count of health workers were collected from all public and mission health facilities. I use the straight-line distance from each DHS cluster surveyed in 2007 or 2013 to the nearest health facility as a proxy for travel time. 10 This distance varies from 53 meters to 40. 7 km. On average, households are located 6 km away from their closest health facility. To ensure respondents' confidentiality, the DHS randomly displace cluster location 11 (see Appendix C, Section 5 for more details), creating a measurement error in the distance to the nearest facility which generates an attenuation bias  (Arbia, Espa, & Giuliani, 2015).
Selection into live birth The policy may have led to selection into live birth if improvement in delivery conditions helped fragile babies survive to childbirth. If these babies would not have survived in absence of the policy, then the probability to observe weaker, high-child mortality risk babies increases in affected areas relative to unaffected ones. In such a case, my sample of exposed children would be negatively selected, potentially leading to underestimate the gains in child health. I test this assumption in two ways. First, using information from the reproductive calendar collected in the 2007 and 2013 DHS survey waves, I create a new database where each observation is now a pregnancy occurring during the last five years preceding the survey, whatever its final outcome, and not necessarily a live birth.
Acknowledgement I am very grateful to  Philippe De Vreyer ,  Élodie Djemaï ,  Pascaline Dupas ,  Clémentine Garrouste ,  Florence Jusot ,  Marta Menéndez  and  François-CharlesWolff , as well as participants at the LEGOS Seminar (November 2019), the Days of the French Health Economists Association (December 2019) and  Dauphine PhD Workshop  ( January 2020 ) for insightful comments. I thank  Barbara Carasso  and  Aurélia Lépine  for providing information on the Zambian health system, the  Monitoring and Evaluation Unit of the Zambian Ministry of Health  for cooperation, and  Sabine Gabrysch  for her precious help in cleaning the administrative GIS data. I gratefully acknowledge the Editor and two anonymous referees for their detailed and thoughtful comments. First version of the paper: November 2019.
Moreover, reference data are not so numerous up to now for the isotopic approach. Considering that the most effective approach is the one based on trace elements in slag inclusions, especially because a high number of reference sets of slag were already analysed and are available for comparison, this paper aims to set a new milestone in the traceability of iron in the western Roman Empire, breaking new ground by performing a first-ever statistical analysis of the data on this same set of artefacts (the iron bars of the Saintes-Marie-de-la-Mer wrecks), based on 12 trace chemical elements, as well as analyzing four additional iron bars, for a total of 13 iron bars. Moreover, this article publish for the first time recent results from research programs on Gallo-Roman iron production areas (see Funding part for the detailed list of these programs), making it possible to analyze an extensive collection of more than 120 smelting slags from six production areas, which constitute a yet unpublished chemical database for determining the origin of iron in the western Roman Empire.
Otherwise, only one sample is taken. In a second step, samples are polished (diamond paste 3 and 1 μm under ethanol). This allows an observation by Optical Microscope and Scanning Electron Microscope to locate and analyse the non-metallic slag inclusions (made of a mix of silicates, oxides and vitrous phases) entrapped in the metallic matrix. The major element composition is determined by Energy Dispersive Spectrometry coupled to SEM (a FESEM JEOL 7100 equipped with an Oxford silicon drift detector, at 15kV with a probe current of 20nA). Prior to any spectrum acquisition, SI were detected by means of image analysis of the backscattered electrons signal. Particle detection and spectra processing were performed using the Aztec Software (Oxford Company). On each spectra the background was substracted using a top hat filter.
The resulting variables were named "xij". Statistical data analysis was performed on xij. The chosen multivariate analysis method was principal component analysis (PCA), sometimes in combination with hierarchical agglomerative clustering (HAC) (FactoMineR and factoextra packages in R software). For PCA, it is verified if the composition of the slag inclusions of a metallic artefact graphically match with the one of other artefacts or the one of the slag of the production sites on all the 2D projections on the PCA dimensions gathering a significant part of the cumulated variance (> 75% generally). For the HAC the chemical compatibility is confirmed when the maximum distance separating two slag from a production area is greater than that separating the inclusion of an object from the nearest slag.
Acknowledgments Our thanks go to HerveLaurent and  Marc Leroy  who have contributed to the construction of knowledge of ancient iron metallurgy in Puisaye and in the Senonais-Pays-d'Othe. Our gratitude also goes to Vincent Serneels who wished to share his documentation and knowledge of the ancient iron metallurgy of Belgium. Without his research in the 1970s, the database on Wallonia presented in this article would never have had such importance and quality.
-Collective research program  entitled " FANUM MARTIS (Nord, France )", directed by  Raphae ¨l Clotuche  ( INRAP -UMR7041   ArScAn ), funded by the  French Ministry of Culture. - ANR-DFG research program  entitled " Circulation of Iron Products in the Iron-Age of eastern France and southern Germany (CIPIA) ", directed by  Philippe Dillmann  ( CNRS -IRAMAT-LMC-UMR5060 ) and  Roland Schwab  ( Curt-Engelhorn-Zentrum Archa ¨ometrie -Germany ). -Collective research program entitled " La metallurgie du fer en Bourgogne-Franche-Comteavant le haut fourneau. Organisation et circulation des productions ", directed by  Marion Berranger  ( CNRS -UM5060 -LMC-IRAMAT-UTBM ), funded by the  French Ministry of Culture  and the  CNRS. -Research program  entitled " Carte archeologique du littoral Camarguais (Bouches-du-Rhone, France )", directed by  Luc Long  ( DRASSM -UMR5140   ASM ), funded by the  French Ministry of Culture.
And n is the number of the criteria of each IPCM. Meanwhile, MRCI is a mean random consistency index, whose values are shown in Table  3. By adopting the package 'AHP survey' in the RStudio, only 15 out of 19 responses satisfied CR of less than 10%, meaning that these official 15 responses would be used for the next analysis. As can be seen in Table  4 , the majority of respondents have working experiences of greater than 11 years (67%). Further, all the subjects are holding the managerial position at their workplace, specifically the head of the division (40%), assistant manager (13. 3%), vice manager (20%), and manager (26. 7%). To conclude, the respondents' profile endorses the validity and reliability of the collected information.
Test the consistency of FPRM. FPRM is acceptable if its CR is less than 10%  [68, 72, 73 ]. Yet, in this situation, we cannot compute CR as done in traditional AHP because inputs in FPRM are fuzzy numbers, not crisp numbers. Instead, we make use of a technique proposed by Kwong and Bai  [73]  to de-fuzzify the fuzzy numbers in FPRM into the crisp numbers. Then, CR can be calculated by the normal way of traditional AHP. According to Kwong and Bai  [73] , the fuzzy numbers a ij = [l ij ,m ij ,u ij ] may be de-fuzzified by the formula: a ij ¼ l ij þ 4 � m ij þ u ij 6 ; i; j ¼ 1; 2;. ; n: ð4Þ We initially calculated FPRMs' L max by using the package 'rARPACK' in the RStudio. After that, Formulas (1) and (  2 ), as exhibited in Section 3. 4, were carried out to estimate CR. For the RL dimension, defuzzification of the matrix ÃRL is: A RL ¼ 1:000 1:140 1:323 1:066 0:886 1:000 1:670 1:452 0:761 0:604 1:000 0:731 0:944 0:699 1:380 1:000 � � � � � � � � � � � � � � � � � � � � � � Then, the maximum eigenvalues of A RL may be estimated as L max = 4.
The practical policy is that port authorities should transfer the limited resources from SAs in Quadrant IV to SAs in quadrant II to enhance PSQ and attract more SCs and freight forwarders. Although our research provides a lot of practical and theoretical references for the port industry of Vietnam, there are several limitations needing to be considered. First of all, this study only collected raw data by interviewing respondents from two kinds of port users, for instance shipping company and ocean freight forwarders. Therefore, further research should extend the respondents from other forms of port users, for example container terminal company, port tourists, and logistics companies inside the port, to better the robustness of the findings. Secondly, because of the utilization of cross-sectional data, this research cannot analyze the changing trend of PSQ over time.
This article asks a simple question that nevertheless has broad implications for historians of premodern continental Europe: What did notaries do? It answers it by applying descriptive statistics, principal component analysis, and clustering techniques to the typological distribution of all deeds preserved in the notarial collections of six French and Italian cities-Paris, Toulouse, Mende, Turin, Florence, and Livorno-for the year 1751, as well as smaller datasets for other dates and locations. The results of this analysis are surprising. In spite of a high degree of consistency in the notarial profession and terminology (a trait that facilitates our comparisons), the notarial style of each city varied greatly. Variations within a single state were sometimes greater than those across state borders.