dataesr/scientific-paragraphs-categorization huggingface dataset:
A. Dedicated or ad hoc laboratories Researchers using oTree do not require dedicated experimental laboratories; they can use existing computer laboratories or rely on tablets. Since touch input works with oTree, tablets can be used without external keyboards, if desired. oTree can be run on low-cost devices such as commodity tablets and mobile devices, thereby reducing hardware costs. Several dozen tablets can be easily transported to any space able to accommodate the participants (such as a classroom or meeting room) and be set up as a temporary laboratory. Another advantage of not requiring a desktop operating system is less time and money spent on maintenance and administration. Desktop operating systems offer great flexibility, but they also require investments in IT tasks such as software installation (e.
B. Online oTree experiments can be conducted online. The experimenter provides each participant a unique start URL. These URLs contain a random alphanumeric code so even if participants communicated with one another, the link would not allow participants to deduce the identity of players in a particular match. There is no set limit on the number of simultaneous participants, thus large-scale market experiments are feasible. As is the case for websites in general, running an experiment with many users requires a server with sufficient resources (processor, RAM, and database). To test whether hardware resources are sufficient and fast enough, we recommend testing the setup with bots (see subsection II). Since the code of experiments (though presumably not all the instructions and payouts) needs no change between online and laboratory settings, running an experiment online can complement running it in the lab.
Because the progress monitor is web-based, multiple collaborators can simultaneously open it on several devices on premises or at remote locations. The admin dashboard is automatically generated for each experiment. Columns included are: the participant ID (the computer number in a laboratory setting), the participant code (a short alphabetic code uniquely identifying the participant), and the current earnings of the participant. Figure  3  displays a principal-agent game. Session interface: While the progress monitor exists in all oTree experiments, the session interface is an optional feature that is convenient to have in some experiments. In many experimental settings, in addition to an experimenter monitoring progress for which the progress monitor is intended, an experimenter needs to receive instructions or provide input for the experiment.
Demo Mode: Experiments can be put online using the demo mode which creates a web page with a static URL. Any visitor to that web page can play the game. For example, for an Ultimatum Game, that web page would have two participant links, one If the game has a study-interface a new URL for that is also created. The demo mode makes it possible to easily share a game with colleagues, referees, and other readers. For example, we use it for our collection of sample games. Not only is the code of these games available, but one can also play them at any time online: demo. otree. org. Using bots, even multi-player games can be put online as supplementary, interactive material. User input and validation: oTree supports all the standard input forms, such as radio buttons, check boxes, drop-down menus, numerical entry, free text entry, date/currency input, email, file upload, and image fields.
To simplify usage of input forms, oTree relies on Django, a widely used Python web application framework. Some custom form widgets, such as Likert scales, go beyond what Django offers by default, but are included in oTree. oTree users are not limited to what Django or oTree include, and can create their own input forms. Figure  5  gives examples of input forms available. If a participant does not fill out a required form or submits an invalid value, the form is automatically re-displayed, highlighting and explaining the user's error. The experimenter can specify what answers are valid. In the case of a numeric input field, the experimenter could, for example, specify that only numbers that are a negative odd integers between -51 and -1 should be valid. Among valid answers, there may be some that are better or more rational than others, but the user can proceed with a chosen answer and is not held back on that page.
If a game is to be played for multiple rounds, participants can either play with the same partners or with new partners. Within a match participants may have different roles such as principal and agent. oTree handles this by a matrix model, where each cell corresponds to a participant, and the rows are groups, while the columns are roles. Dynamic graphics: In many experiments it is useful to have visual content created and updated during the experiment. In a market game, for example, participants could be shown a graphic depicting the evolution of prices. For this purpose, oTree integrates HighCharts, a JavaScript-based service. 6  Figure  6  is a screenshot taken from round six of a 50-round game. Sample games: oTree includes a library of dozens of standard economics games. To see these games and play them, go to http://demo.
otree. org/demo/. Incidentally, these games are put online using oTree's demo mode. Researchers can use the code of these sample games as templates for their own games. Those who are developing completely new games are also encouraged to review the sample games to learn about recommended coding styles. Localization: Of course, oTree applications can be translated to multiple languages and oTree has multiple features to ease translation and localization. A single switch controls the language in which the application is currently displayed. This is useful in FIGURE  6. DYNAMIC GRAPHICS many scenarios. For example, an experimenter can deploy the same experiment in the U. S. , Germany, and China with all participants reading in their native tongue. Or, one can deploy an experiment in German but send English-speaking colleagues a demo link in English and publish English screen shots in a paper reporting the experiment.
As most programmers comment in their code, oTree intelligently extracts these comments and adds them to the documentation. Open source: Sonnenburg et al. (  2007 ) have argued that in scientific applications, the source code should be available for inspection and available free of charge to enable replication and extension. Janssen et al. (2014)  point out that that binary software cannot be checked by people other than the software authors. Lerner and Tirole (2005)  argue that open-source software will grow strongly, and that academic economists could both learn and benefit from the model. Thus oTree is open source, meaning that the source code is freely available and anyone can add to it subject to our open-source license terms (http://www. otree. org/license). To develop oTree, we use GitHub, a web service familiar to most programmers which hosts many open-source projects and offers source code management and distributed revision control.
III. Technology and programming This section gives an overview of the oTree architecture and programming. For details, and to get started, consult the website, oTree. org, download the source code that comes with dozens of sample games, and consult the wiki at oTree. org/wiki. oTree's programming model follows the Model-View-Controller approach as discussed in  Leff and Rayfield (2001)  for the specific case of web applications. The controller resides in the core of oTree. Each oTree application consists of a models. py file, a views. py file and several html-templates-one for each screen. The models. py file defines the players, variables, and their data types; defines the validation logic; and specifies the arithmetic operations to be performed. The view is given by the views. py file and the html-templates.
A. Skills required to program in oTree oTree is based on Python, a widely used programming language that is available as open-source software from the Python Software Foundation. Python is often the first language taught in introductory computer sciences courses. 7 Learning Python might be a good investment for empirical and experimental researchers as it is useful not only for oTree, but for many tasks such as automatic data extraction and web-scraping. oTree is designed to be simple and to be accessible to people with basic programming experience. Researchers who prefer to hire a programmer for oTree, rather than code themselves, should hire someone who knows Python. For best results, the programmer should also be familiar with Django, which is the most popular Python-based web development framework.
B. Hardware requirements The only requirement on participants' computers is a web browser capable of HTML5. Anything that works in HTML5 can be included in oTree, for example hyperlinks, dialog boxes, tables, images, audio, and video. Video recording is still experimental in HTML5. JavaScript, Java, and Flash are supported by oTree, but programmers should be aware of the limitations operating systems impose (e. g. , Flash does not run on iOS devices). A good recommendation for oTree experiments-and for any website-is to use JavaScript if necessary, but not Java or Flash. Computer requirements for the server depend on the number of participants and the experiment; often a standard laptop will suffice. If reliable internet is available, the easiest solution is often to rent a server in the cloud.
D. Simple code oTree's code is remarkably simple as it builds on Python. Compared to z-Tree, oTree is less specifically tailored to some experiments but arguably more general. In z-Tree, users spend considerable time and effort implementing solutions to problems that have now become easy using modern programming languages. To give an idea of the simplicity of oTree, consider the standard experimental requirement of playing a random subset of rounds in a game with many rounds, the code for this is shown in figure  7. 9   oTree works with standard code editors such as PyCharm. 10 A code editor makes programming easier by providing live error checking, syntax highlighting, interactive debugging (to test the effect of each line of code), and code reorganization functionalities (such as the ability to easily rename a variable).
oTree integrates with the auto-complete functionality of PyCharm. Suggestions of variable names are presented as code is typed. If oTree encounters an error during execution, an error page pinpointing the source of the error is shown. F. Collaborative development oTree is developed using Git, a source-code versioning system. This encourages good backup and versioning practices, and allows developers to synchronize files across computers, develop collaboratively, manage separate branches, and merge synchronization conflicts. We invite other researchers to join us on GitHub, but this is not a requirement for using oTree.
*   All authors are at the Center for Law and Economics, D-GESS, ETH Zurich, CH-8092 Zurich. For comments on the oTree software or the paper, we thank the people at the experimental econ laboratories in Magdeburg, Hamburg and ETH Zurich, Donja Darai, Kelly Reeve, Rok Roskar, Alexander Sandukovskiy, and Stefan Wehrli. Stefan Bucher provided superb research assistance.
These macroeconomic considerations are reflected in employers' behaviour in arbitrating between costs and benefits when deciding on whether to hire or fire. But, they also affect the choice of the type of hiring and/or separation used, by changing the relative cost between different types of separation for example. In this context, and given its strong growth in the CDI terminations  (Sanzeri, 2013) , RC appears to be a success, and its consequences on the labour market are not insignificant. This is especially true in France where emploment protection legislation (EPL) is often criticised for its rigidities. Yet, few studies have analysed the effects of this new legal rule on firms' behaviour, using firms' datasets. This article therefore provides some initial understanding and assessment of the economic effects of RC.
One of its novelties is to rely on two types of theoretical and empirical literature: i) the traditional literature concerning worker and job flows, and ii) more recent work related to the economics of law, studying the strategic use of the Accepté (le 22/09/2015) pour publication dans l'International Journal of  Manpower, vol. 37, n° 8, 2016 -12, p. 1365 -1386. DOI : http://dx. doi. org/10. 1108 /IJM-11-2014-0224. 2 different types of separation by employers. More precisely, the purpose of the article is to study the possible impact of the introduction of the RC on two decisions by employers: i) the decision to separate with an employee or even to destroy a job, and ii) the use of one form of separation rather than another. The approach I use here is essentially empirical, focusing on an econometric analysis of a sample of firms constituted by matching a database on employee movements (the EMMO-DMMO) with surveys of company accounts (EAE-Esane).
5 Therefore, firms that used separations for economic reasons, whether it be under the legal form of a dismissal for economic reasons or by RC, will create fewer jobs than others. I test these two hypotheses with a sample of firms constructed from matching two databases on workforce movement in establishments and on firms' income statements. To this end, I run a propensity score matching method to construct two similar firm groups, which differ only in the fact that one uses RC and the other does not. Next, a difference-in-differences approach is Accepté (le 22/09/2015) pour publication dans l'International Journal of  Manpower, vol. 37, n° 8, 2016 -12, p. 1365 -1386. DOI : http://dx. doi. org/10. 1108 /IJM-11-2014-0224. 9 used: I compare the evolution of employment decisions of the two firms' groups in order to identify the specific effect of RC in user firms.
Data and sample construction Matching data for establishments on workforce movement (EMMO-DMMO) 6 and data on firms' accounts and finances (EAE-Esane) 7 provides a database that brings together indicators of the human resources management, job flows and firms' economic performance. The first database contains monthly or quarterly information on entries (by type of contract) and on exits (type of contract terminations), for establishments in mainland France. The second database collects economic and financial information of firms' income statements. Several steps were taken to match these two bases. First, the database was constructed at firm level: i. e. , the information from the EMMO-DMMO database on establishments is aggregated at firm level. Next, workforce movements are annualized to compare them with the annual economic indicators constructed from EAE-Esane.
Finally, various stages in the matching process lead to the removal of establishments from the EMMO-DMMO database, when they are not found to belong to any firm in the EAE-Esane database, and vice-versa for some firms that cannot be matched with any establishment in the EMMO-DMMO database. Finally, from the matched database, only firms with data for consecutive years  (2006 to 2009)  are retained. I was thus able to obtain a sample comprising 6,302 firms, which were tracked for four years (balanced panel). The sample is not representative of all French firms. For example, it over-represents the industry sector (almost 50 % of firms) and large companies (almost 50% are firms with 100 or more employees). 8 In addition, variables for workforce management and job flows are all lower than levels found in all French firms (see Appendix A).
We use a unique, cross-national dataset, the OECD Programme for the International Assessment of Adult Competencies (PIAAC). PIAAC contains a measure of self-reported health and educational attainment but also, and crucially for our study, cross-nationally comparable measures of cognitive skills and interpersonal trust. The paper is structured as follows. We first examine the education, skills and trust gradients in self-reported health and whether these differ across countries. We then examine if the relationship between education/skills and health are mediated by levels of interpersonal trust (mediation analysis). Finally, we assess potential heterogeneous treatment effects (moderator analysis) to understand if the education and skills gradients in health are due to better-educated and better skilled individuals enjoying higher levels of interpersonal trust.
Data We use data from the OECD's Survey of Adult Skills (PIAAC). Around 166 000 adults aged 16 to 65 were surveyed in the following 24 countries/national sub-regions: Australia, Austria, Belgium (Flanders), Canada, the Czech Republic, Cyprus, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Japan, Korea, the Netherlands, Norway, Poland, the Russian Federation, the Slovak Republic, Spain, Sweden, the United Kingdom (England and Northern Ireland), and the United States. Data collection took place from 1 August 2011 to 31 March 2012 in most participating countries, although in Canada data collection took place from November 2011 to June 2012, and in France it took place from September to November 2012. The target population for the survey was the non-institutionalized population, aged 16 to 65 years, residing in the country at the time of data collection, irrespective of nationality, citizenship or language status.
The survey was administered in the official language or languages of each participating country and some countries gave respondents the possibility of participating in one of the widely spoken minority/regional languages (see  [71]  for technical details). In analyses presented in the paper we exclude individuals from the Russian Federation because of data concerns  [71]. PIAAC has two main components: a background questionnaire and an assessment of literacy, numeracy and problem solving in technology-rich environments. The questionnaire was administered first in a CAPI (computer-assisted personal interviewing) format and response time ranged from 30 minutes to 45 minutes. Upon completion of the questionnaire, respondents sat a cognitive assessment, which took around one hour to complete. Depending on their computer skills, the assessment was delivered either on a laptop computer or as a fillin paper booklet.
Conclusions and Discussion Our paper builds on previous literature examining cross-national differences in education gradients in self-reported health. We use a new dataset containing measures for 23 countries of the number of years of schooling individuals attended, the literacy proficiency they demonstrate in an internationally agreed and validated assessment and their self-reported level of interpersonal trust to disentangle the independent relationship between educational attainment and cognitive skills and self-reported health and examine the extent to which human and social capital jointly explain within-country disparities in self-reported health status. The first contribution of our paper is that it clearly illustrates that while individuals who have attended school for longer and who demonstrate better cognitive skills generally report being in better health than those who have attended school for less and who have lower literacy skills, education and skill gradients differ markedly across countries.
These bodies follow international prescriptions in terms of statistical definition and methods, but to varying degrees and since different years. Definitions of categories remain different from one country to another and even when they are alike, the available data on the local scale varies. As an example, incomes are documented in a large number of ways: in the Near East we could only find net incomes in Israel, daily wages in the occupied Palestinian territory, and households' income in Jordan. In order to make comparable series and maps, we harmonised data by keeping the regional distribution of the data provided for a given country, and applying it to the national value found in the same international database selected to apply to all neighbour countries-Gross National Income from World Bank data in that case.
In addition, preliminary results from on-going longer-term assessment of vaccine safety in these trials, including an extension trial of the phase IIb, have been reported  [22]. The World Health Organization (WHO) states that specific potential safety issues should be taken into considerations in the assessment of candidate dengue vaccines and long-term safety surveillance  [23, 24]. These issues include possible vaccine-associated dengue-like disease due to vaccine viremia, sensitization or enhancement of dengue illness, and an increased likelihood of severe disease in young children. In addition, for the CYD-TDV vaccine, viscerotropic and neurotropic disease should be assessed due to the YFV backbone of the CYD-TDV. Here we report a pooled analysis of safety data from 18 phase I, II and III clinical trials that assessed the candidate CYD-TDV vaccine.
One trial was non-randomized, with participants analyzed on the basis of previous vaccination with a monovalent DENV1 or DENV2 vaccine, YFV vaccine or flavivirus sero-negative status  [13]. All trials except one were registered on ClinicalTrials. gov or EudraCT  [11]. All 18 trials involving vaccination included in this analysis were approved by the relevant ethical review committees, institutional review boards, or both, as well as by national health autorities. They were carried out in accordance with the relevant International Conference for Harmonization guidelines and the principles of the Declaration of Helsinksi.
In the three efficacy trials, reactogenicity data were collected for participants who had been randomized to the immunogenicity/reactogenicity subset  [19] [20] [21]. The severity of solicited reactions was graded as 1, 2 or 3 (Table  2 ). Analyses are reported by age group, defined using the age at enrolment, and, in trials with data available for specific subgroups, analyses are also reported by baseline dengue serostatus and post-injection viremia. Although in the original trials the safety events were coded using different versions of MedDRA, the events were re-coded using version 14. 0 to ensure homogeneity across the trials. Allergic reactions and anaphylaxis within 7 days of vaccination and severe dengue disease virologically-confirmed any time after dose 1 were considered as adverse events of special interest (AESIs).
Biological safety Biological parameters were assessed at pre-specified time points in subsets of participants in three main trials and all secondary trials (Table  1 ). Based on changes observed in phase I trials and on biological abnormalities that can mimic dengue disease, the parameters assessed were creatinine, liver function markers, i. e. , alanine aminotransferase [ALT] and AST, and bilirubin and hemoglobin [Hb], hematocrit, white blood cells [WBCs], lymphocytes, neutrophils, and platelets. Biological parameters collected from participants with symptomatic dengue disease were not included in this pooled analysis. Since the parameters were assayed by local laboratories using local standards and the normal reference ranges varied between trials, these biological data were standardized for use in the quantitative and toxicity grading analyses.
CYD-TDV vaccine viremia Vaccine viremia was assessed at pre-specified time points in nine phase I-III trials, in participants with acute febrile illness in six trials conducted in endemic areas (Table  1 ). Data after doses 1 and 2 were analyzed since vaccine viremia is mainly observed after these injections. Data were analyzed for time points for which vaccine viremia was consistently collected across studies, i. e. , D7 (D5-D11) and D14 (D12-D17) in accordance with WHO recommendations  [23]. Vaccine viremia was also assessed in individuals with acute febrile episodes within 28 days after vaccination, in trials performed in dengue endemic regions to determine if the fever was vaccine-related (positive vaccine viremia) or was due to dengue infection, in accordance with WHO guidelines  [7, 9, 10, 15, 16, 21, 27].