dataesr/scientific-paragraphs-categorization huggingface dataset:
To test for Sunni opportunity costs, we gather data on youth unemployment rate estimates from World Bank. As we have no data on the unemployment rate of Sunni populations, we follow  Gouda and Marktanner (2019)  by computing the interaction between these two variables, a factor they found to correlate with the number of foreign fighters joining ISIS. (autocracy) to 10 (democracy). Regimes types have been found to have mixed influence on terrorism. On the one hand, democratic regimes allow freedom of association, making the organization of an insurgency less costly, and have an institutional setting in which terrorism may be more visible and efficient, thanks to higher levels of press freedom and higher audience influence on policy  (Chenoweth 2013 ). On the other hand, democracies are also more inclusive and offer legal channels to voice political grievances  (Gaibulloev, Piazza, and Sandler 2017).
Analysis Consortium (TRAC 2019) which is, to our knowledge, the most extensive database on terrorist organizations (their history, ideology, targets, etc. ), covering more than 4,500 groups. The GTD includes a great number of small groups, on which information about the ideology is not always available. For that reason, we exclude minor terrorist groups that perpetrated five attacks or less over 1992-2006. Table  A3  lists the identified jihadist groups for the study period. This process leads us to identify 372 attacks. We sum the count of attacks per country and year to construct our dependent variable. To measure military interventionism, we follow  Piazza and Choi (2018)   (Maoz and Henderson 2013). Based on this data, we construct a country-year dummy coded 1 for countries military involved in one or more politico-strategic intervention in Muslim countries, and 0 otherwise.
We expect this variable to be positively related to jihadist domestic terrorism. We use the same socio-economic causes than in study 1, except that we focus on Muslim populations in general rather than on Sunni populations 11. We only make two changes regarding the control variables. We do not include a measure of territorial distance since our dependent variable gathers attacks from groups implanted in different areas. Moreover, as Study 2 focuses on terrorist attacks performed by groups that were territorially implanted in various countries facing civil wars, we control for a dummy variable indicating the occurrence of a civil war in a given country-year based on the Major Episodes of Political Violence database  (Marshall 2017). Major episodes of political violence "involve at least 500 "directlyrelated" fatalities and reach a level of intensity in which political violence is both systematic and sustained (a base rate of 100 directly-related deaths per annum)"  (Marshall 2017: 7 ).
In line with this argument, our results demonstrate that the distance of a country from the organization's headquarters is associated with less affiliated terrorists' attacks, but it does not affect the number of lone wolves' attacks. Moreover, the choice of the right strategy does not only depend on the characteristics of the targeted country, but also on those of the organization itself. The less costly strategy is preferred when the organization is weakened. Data from the GTD support this interpretation. This lead us to discuss our second key finding, namely that jihadist domestic terrorismdefined by an identity relationship between the venue, target, and perpetratorsis not immune from a strong international dimension. Domestic terrorist attacks are used in retaliation for military interventions in Muslim countries.
Piazza (2012)ntage of the dataset is that it allows distinguishing levels of discrimination suffered from different religious minorities by country, rather than computing an aggregated national score of discrimination. However, the major limitation is that the data is time-constant, the last update dating back from 2006. Hence, it does not take into account recent national variation in minority discriminations. Based onPiazza (2012), we construct a binary variable coded 1 for countries in which at least one Sunni minority face some level of political, economic, linguistic or religious discrimination. Other countries, either having no Sunni minority at risk or in which Sunni minorities do not face discrimination, are coded 0.
(Kisangani and Pickering 2007)tary Intervention Dataset(Pickering and Kisangani 2009), which lists all cases in which national military forces were moved into foreign countries from 1947 to 2005. Military interventions fall in two categories depending on their motives(Kisangani and Pickering 2007). On the one hand, politico-strategic interventions are launched for a least one of the following issues: diplomatic issues, domestic political issues, regime change issues,.
prevention. Dordrecht : Springer Science  and  Business Media. Starr-Deelen , Donna. G. 2018. "The Rise of ISIS". In Counter-Terrorism  from the  Obama Administration  to President Trump, Dordrecht: Springer:  19-26. START (2017 ). Global Terrorism Database, https://www. start. umd. edu/gtd. START (2019). Global Terrorism Database, https://www. start. umd. edu/gtd. TRAC. 2019. "Groups. "Tracking terrorism, May 20. https://www. trackingterrorism. org/groups. Verwimp, Philip. 2016. "Foreign fighters in Syria and Iraq and the socio-economic environment they faced at home: A comparison of European countries". Perspectives on Terrorism, 10(6):  68-81. Von Einsiedel , Sebastian,  Louise Bosetti ,  James Cockayne ,  Cale Salih , & Wilfred Wan. 2017. Civil War trends and the changing nature of armed conflict.
Piazza (2012)ntage of the dataset is that it allows distinguishing levels of discrimination suffered from different religious minorities by country, rather than computing an aggregated national score of discrimination. However, the major limitation is that the data is time-constant, the last update dating back from 2006. Hence, it does not take into account recent national variation in minority discriminations. Based onPiazza (2012), we construct a binary variable coded 1 for countries in which at least one Sunni minority face some level of political, economic, linguistic or religious discrimination. Other countries, either having no Sunni minority at risk or in which Sunni minorities do not face discrimination, are coded 0. (Benmelech and Klor 2018)Choi and Piazza 2017;Ghatak and Prins 2017;Ghatak, 2016) the terrorism-discrimination nexus(Piazza 2011;Piazza 2012;Choi and Piazza 2017;Ghatak and Prins 2017;Ghatak, 2016)by relying on the Minorities at Risk Database (Minorities at Risk Project 2009).
(Kisangani and Pickering 2007)tary Intervention Dataset(Pickering and Kisangani 2009), which lists all cases in which national military forces were moved into foreign countries from 1947 to 2005. Military interventions fall in two categories depending on their motives(Kisangani and Pickering 2007). On the one hand, politico-strategic interventions are launched for a least one of the following issues: diplomatic issues, domestic political issues, regime change issues, Piazza and Choi (2018)strategic issues and territorial issues. On the other hand, socio-economic interventions refer to at least one of the following issues: humanitarian issues, social or economic issues. AsPiazza and Choi (2018)find that only politico-strategic interventions are associated with transnational terrorism, we specifically analyze these instances.
Isotopic data were obtained from published  (Dudd, 1999; Spangenberg et al. , 2010; Craig et al. , 2012; Choy et al. , 2016)  and unpublished data and using fatty acid concentration values obtained from the USDA database (https://fdc. nal. usda. gov/). of C 16 and C 18 fatty acids in these sources. The theoretical mixing model presented in Fig. 6  shows that when even a modest amount (ca. > 10%) of ruminant fats are mixed with fish oils, the Δ 13 C values can shift to below -1‰ (Fig. 6b ). While, in contrast, when fish fats are mixed with plants or non-ruminant fats, these do not shift the Δ 13 C values within the range observed in the pottery i. e. < -1. 1‰. (Fig. 6c  and d ). Therefore, the interpretation that the pots containing aquatic biomarkers were used for processing a mixture of fish and ruminant resources, either together or through successive uses is supported.
In turn, these insights would greatly complement the large bioarchaeological datasets that document the diet, health and mobility of individuals from the Kitoi and Cis-Baikal's subsequent Late Neolithic and Early Bronze Age mortuary traditions (i. e. the Isakovo, Serovo, and Glazkovo). Mixing Model. The mixing model was performed using R studio (version 3. 5. 1). Further information is provided in the Supplementary Material, Table  D.
Acknowledgements This research was funded by the  European Union 's  EU   Framework Programme for Research and Innovation Horizon 2020 under Marie Skłodowska-Curie Actions Grant Agreement No 676154 (ArchSci2020 program ). It forms part of  M. Bondetti 's PhD project, supervised by  Oliver E. Craig  and  Peter D. Jordan , and hosted at the  University of York (BioArCh) , and the  University of Groningen (Arctic Centre ). We would also like to thank  Frits Steenhuisen  ( Arctic Centre, University of Groningen ) who produced Fig. 1,  Marise Gorton  ( University of Bradford ) for undertaking the bulk stable isotope analyses, and  Matthew Von Tersch , for his assistance with some aspects of the laboratory work ( BioArCh, University of York ). While completing final drafts of this paper P. Jordan was supported by a  JSPS   Invitational Research Fellowship (Long-Term ),  Research Theme: "Neolithization Trajectories in NE Asia and Hokkaido " (Award:  L19515 ), hosted by  Hokkaido University  (2019University ( -2020)).
Burnt bones, charcoals and charred residues from the pottery sherds recovered in the spoil heap in which the bird carving was found were radiocarbon dated (Fig 1c, Table  1 ) at three dating laboratories: the Institute of Accelerator Analysis Ltd. , Kawasaki City, Kanagawa, Japan (IAAA), the University of Tokyo Radiocarbon Laboratory (TKa), and the Beijing University Radiocarbon Laboratory (MTC), China  [40] [41] [42] [43]. The thirty-six available ages, three of which obtained in the framework of this study (see below), were calibrated with the OxCal 4. 3. 2 online software  [44]  using the IntCal13 atmospheric calibration curve  [45]. With the exception of a single old age obtained from a charcoal sample (IAAA-100080: 28,690±120 14 C years), not included in Fig  1c , two distinct sets of ages are identified by the dated material.
5 μm. A copper filter of 0. 1 mm was used and 1875 projections were taken at 360˚. The reconstruction of the volume was performed with the Datos | Rec software of GE. 3D visualizations were then performed within the Avizo 9. 1 (FEI) workspace. A simplified 3D surface was also generated (S1 Data) with the MiKTeX Console 2. 9. 7076. The object was photographed with a Sony E 30 mm with a macro-lens, and examined and photographed with a motorized Leica Z6 APOA equipped with a DFC420 digital camera linked to LAS Montage and Leica Map DCM 3D computer software. Images showing various aspects of the figurine were imported into Adobe Illustrator and used to make a tracing of the areas bearing traces of manufacture identified under the microscope. This tracing was compared to the original specimen under a microscope and corrected as required.
High-resolution surface topography of selected areas was obtained with a Sensofar S neox confocal microscope driven by SensoScan 6 software (Sensofar) in order to better visualize and characterize traces of manufacture and use wear. Data acquired from the various imaging methods were compared to establish the technique of manufacture used and the orientation of the motion on each identified area. Distinction between traces of manufacture and alterations resulting from use was based on diagnostic features identified on ethnographic, experimental and archeological bone items  [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62]. When two or more techniques were identified on the same area, partial obliteration of the original anthropogenic modifications by traces generated through the subsequent application of another technique clarified their chronological ordering.
09L5鸟-01 ). All Funding: This research was supported by grants given to ZL by the  National Natural Science Foundation of China  (grant number: 41630102 and 41672020; http://www. nsfc. gov. cn/english/site_1/index. html),and to HF by the  Shandong University 111 Project  (grant number:  111-2-09 ; https://en. sdu. edu. cn/). Funding was also provided to LD and FD by the  Sino-French PHC   Cai Yuanpei program  (grant number:  36707NF ; https://cn. ambafrance. org/-Le-programme-Cai-Yuanpei-1628-), the  Programme Investissements d'Avenir IdEx of the Bordeaux University  (https://idex. u-bordeaux. fr/fr/),and the  Research Council of Norway through its Centre's of Excellence funding scheme, SFF Centre for Early Sapiens Behaviour (SapienCE) , project number  262618  (https://www. forskningsradet.
no/en/). L. D. was granted financial support from the  China/Shandong University International Postdoctoral Exchange Program  (http://www. chinapostdoctor. org. cn/) and the  Sino-French PHC Xu Guangqi  (grant number:  41230RB ; https://cn. ambafrance. org/-Le-programme-XU-Guangqi-). PACEA ( UMR5199   CNRS ) is a Partner team of the  Labex LaScArBx-ANR  n˚ANR-10-LABX-52 (https:// lascarbx. labex. u-bordeaux. fr/). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
In this paper, we investigate selective exposure to news among citizens with populist attitudes. The selective exposure literature is full of evidence showing pronounced effects of partisan predispositions on news selection  (Stroud 2017). In light of recent developments on the supply side of politics such as the electoral successes of populist parties, populist attitudes might be a crucial factor guiding information selection. Whereas previous research has relied on survey-based self-reports of media exposure, we use digital behavioral data from the Web browsing histories of 7,729 study participants in France, Germany, Italy, Spain, the United Kingdom, and the United States. This has several advantages: First, such "Web tracking" data provide more reliable measures than commonly used self-reports on media exposure, which have several limitations  (Prior 2009; Scharkow 2016).
Web Tracking The collection of Web tracking data for this study was done by the survey company Netquest (an affiliate of GfK) in full compliance with EU GDPR (General Data Protection Regulation) regulations. 4 The company is the only one that maintains Web tracking panels in all of the countries under study. Loyal panelists in the regular online access panel are incentivized to also install tools for the tracking of Web site visits on desktop computers as well as Web site visits and app use on smartphones and tablets. Participants are informed about the nature of the data collection and asked for their explicit consent to participate in surveys and Web tracking. The data include the full URL, the name of the domain, the time of access, and the duration of a visit (on desktop computers, an active browser tab).
For a better understanding of the distinction between the two online only news types, an example is that we code the HuffPost as a digital-born outlet and Breitbart News as hyperpartisan news. Our coding approach covers 93 percent of all Web site visits. A codebook with definitions for each category and a flowchart for the coding can be found in Online Appendix Section 2. The list of coded news domains is shared in the Supplemental Material. It could well be the case that the online behavior of panelists who agree to install tracking tools differs from the general population of Internet users. However, we validated that the visits of panelists to news domains are comparable with national benchmarks (Online Appendix Section 3). The popularity of news domains in our data corresponds strongly with Alexa data and another benchmark available for Germany, data from the "Informationsgemeinschaft zur Feststellung der Verbreitung von Werbeträgern" (IVW), a Joint Industry Committee to which media providers, advertisers, and advertising agencies submit their original visit data to evaluate their marketing value.
Survey The survey company is still in the process of expanding their Web tracking panels in our target countries so that there is quite a bit of variation in the sample sizes as well as their demographic composition per country (Online Appendix Section 1). We addressed this issue in two ways. First, the sampling of panelists was determined by national census statistics as far as possible. As some of the quota cells were not fully available (e. g. , lower education) and due to the overall limited number of tracked desktop users in some countries, we still have pronounced deviations from national census data for some demographic groups. Therefore, after the field period, we poststratified our samples according to population weights based on census data (Online Appendix Section 1). We invited participants in the Web tracking panels to a survey on media and politics.
Analysis We link the survey and Web tracking data via a unique anonymized panelist ID. The final analysis is based on the survey responses from 7,729 panelists and approximately 150 million desktop URL visits made by them between March 15 and June 16, 2019. 5  To construct our dependent variables, we aggregate all visits by a respondent to domains belonging to one of the six news types we distinguish. Because the dependent variables are heavily skewed, we use count models for the multivariate analysis. Likelihood ratio tests show that the over-dispersion parameter is significant in each of the models (each p <. 001). Therefore, negative binomial regressions are preferable over Poisson models. We include several control variables. Political interest was measured on a 4-point scale in all countries, ranging from "not at all interested" to "very interested.
Moreover, the relationship between populist attitudes and visits to hyperpartisan news sites was not robust across countries. Like other problematic aspects of digital media such as self-segregation or exposure to disinformation, consumption of hyperpartisan news is still a fringe phenomenon. We also acknowledge several limitations. We only measured media exposure at the domain level and did not take into account which individual articles participants visited. In further research, one could use machine learning to classify all articles from a given domain as political or not  (Budak et al. 2016; Flaxman et al. 2016 ). We also could not directly measure exposure to news within social networking sites like Facebook. Our findings were based on a non-probability sample, as for such a sensitive data collection, the informed consent of participants is required.
Acknowledgments We thank four reviewers,  Cristian Vaccari ,  Richard Fletcher ,  Anne Schulz , and participants at the  European Consortium for Political Research (ECPR) General Conference 2019 ; the European Political Science Association (EPSA) Annual Conference 2019; the workshop "Digital Threats to Democracy"; the workshop "Linking Survey and Context Data"; and the  Eurolab Conference  for helpful comments. Excellent research assistance was provided by  Céline Widera.
Hinsley et al. (2019)  also mention that the non-sensitive items should not themselves be susceptible to social desirability bias. We account for those elements in our double-list experiment design. Similar to the sensitive item, the non-sensitive items on the two lists were chosen by making sure that they referred to the sensitive behaviour of interest: sex work for the Senegalese dataset on condom use among FSWs and family planning for the Burkina Faso dataset on physical IPV. Also, the design included at least one non-sensitive item that most participants would agree with ("I prefer that the client pays me before sexual intercourse" on list A and "The majority of my clients are Senegalese" on list B for the Senegalese dataset; "Contraception can reduce the number of pregnancies" on list A and "Getting pregnant right after childbirth can cause health problems for the mother" on list B for the Burkina Faso dataset) and one non-sensitive item that most participants would disagree with ("Monday is the day when I have the highest number of clients" on list A and "I usually spend the whole night with my client" on list B; "The same condom can be reused several times" on list A and "I would like to have more than 10 children" on list B for the Burkina Faso dataset).
Data collection In both studies, the questionnaire data were collected using electronic devices. We randomised the allocation of participants to the treatment or control group based on their "arrival" number. Each enumerator had to interview a specific number of participants and the arrival number refers to the order in which respondents were added to the enumerator's empty ranking sheet. Odd numbers were allocated to the treatment group of one list and the control group of the other list, whereas even numbers were assigned to the other groups. Thus, the arrival number was not manageable by the enumerator, as they did not decide who would be the next respondent to be interviewed, this ensured that the treatment assignment was orthogonal to the enumerator. Every interview lasted 1. 5 hour on average and aimed to collect socio-economic, behavioural, and psychological information.
Survey among female sex workers in Senegal This first data set includes 495 FSWs working in Dakar, with the sample stratified by registration status (registered versus non-registered FSWs). Registered FSWs were recruited using medical records from four (out of the five) STI centres located in the suburbs of Dakar (Rufisque, Pikine, Mbao, and Sebikotane), while non-registered FSWs were recruited with the help of FSW group leaders and NGO staff. All the FSWs were asked to come to a healthcare center, where they were interviewed in dedicated private rooms. Data collection was performed in August 2017.
Survey among married or cohabiting women in rural Burkina Faso Data collection was undertaken between May and July 2018 in the province of Houet, located in the southwest of Burkina Faso. In this region, we randomly selected six rural districts, and within each selected rural district, we randomly selected five villages. In each of the 30 selected villages, we conducted a census that listed all households, with information about the cohabiting or married couples in each household (some households have multiple couples). We then randomly selected 2997 households that included a married or cohabiting woman. As these data were collected to roll out a randomised controlled intervention to study couples' fertility decisions, we also imposed the following inclusion criteria: the married or cohabiting woman (i) must be currently living with her partner/husband; (ii) must not currently be pregnant; (iii) must not be menopausal or sterilized and must not have had a hysterectomy; and (iv) must never have been told by a health worker that she has a health condition that contraindicates the use of modern contraceptives.
List experiment assumptions In Appendix A1, Table  A1  displays the characteristics of the Senegalese FSWs in group 1 (treatment for list A and control for list B) and group 2 (control for list A and treatment for list B). Similarly, Table  A2  presents a series of relevant characteristics for the Burkina Faso dataset. We observe that in both datasets, the observable characteristics are balanced between the treatment and control groups. The joint significance tests for a large share of the variables presented at the end of Tables  A1  and A2  confirm the success of the randomisation (assumption (i)) for both surveys. Based on Rows 5 and 6 of Table  A3 , which reports the results of the two statistical tests presented by  (Blair and Imai, 2012) , we can conclude that there is no design effect issue (assumption (ii)).