dataesr/scientific-paragraphs-categorization huggingface dataset:
| Overall design We utilized a dataset collected during the initial COVID-19 lockdown in France (April-May 2020). 1  The study involved N = 1154 participants, selected to mirror the demographics of the French adult population in terms of age, gender, and living area, courtesy of the Viavoice polling institute. On average, participants were 50. 21 years old (SD = 16. 9). About 20% of the sample comprised individuals under 35, with an additional 40% falling under 55 years of age. The experimental tasks and questionnaires were executed via a web-based platform. Each participant engaged in two incentivized tasks: the portfolio choice task and the CTB task. Additionally, participants completed three self-reported questionnaires to gauge their risk attitudes in general and in the domains of finance and health.
Our data collection took place during the initial Covid-19 pandemic lockdown (April-May 2020) in France, and the pandemic introduced a substantial health BR. This type of risk is unavoidable and uninsurable, and given that older individuals were more susceptible to the effects of Covid-19, their actual risk tolerance might be higher than what our elicited risk tolerance measures captured. This consideration is particularly relevant because the presence of a BR, as demonstrated by  Beaud and Willinger (2015)  in a student sample of 279 individuals, can lead to a substantial proportion of participants (80%) exhibiting risk vulnerability-meaning their risk tolerance decreases significantly when exposed to a BR. Consequently, our risk preference measurements are likely to reflect an increased degree of risk aversion resulting from the presence of the health BR.
Property and Prices This section analyses a hand-written register of sales deeds registered between 1802 and 1804, with the majority (60 percent) registered in 1803. 70 There were sixty-four sales deeds in this register, all of which were digitized by the author. Key information about the properties was extracted from the deeds, categorized, and prepared for data analysis. 71  These sales deeds were less formulaic than the permissions to sell in the petition book, although certain textual formulae were used. All the sales deeds listed the names of the buyer(s) and seller(s) of the property and the price. At this time in Bombay, property transactions involved either houses or oarts. In the case of houses, it was often specified whether the property was inside or outside the town walls, highlighting the spatial importance of the fortifications in Bombay's land market, as mentioned earlier.
Many of the scientists within the BHI have also been involved with the Event Horizon Telescope (EHT), a long-running, planetary-scale virtual telescope composed of widely-dispersed observatories. The EHT observatories, eight on six sites as of 2017, and expanded to eleven observatories since, register millimeter electromagnetic waves from the same source by putting the data on hard drives with precise time stamps given by a hydrogen maser. The drives are then transported to central computing facilities where supercomputer "correlators" align the recorded signals. These aligned data can then be used to create images. In April 2019, the EHT Collaboration released the first ever picture of a black hole, M87*, the 6. 5 billion solar mass compact object at the center of the elliptical galaxy M87 in the constellation Virgo  [19].
Governance Well-structured governance is key to the future of collaboration. A main task for the Collaborations focus group will be to systematically analyze the organizational structure of various similar collective entities, including LIGO-Virgo, EHT, ATLAS, CMS, CERN, IPCC, the UN, Hubble and JWST, to identify their main benefits and drawbacks. Surveys conducted among ngEHT members, based on a similar survey conducted within the EHT collaboration, will also provide valuable data moving forward. These lessons will be synthesized into the optimal governance model for the ngEHT, keeping in mind the desiderata and worries described in the previous subsections. To give the reader a tentative first impression of what such a governance model might look like, we sketch here an initial suggestion.
Acknowledgments: We want to recognize the early and important contributions of  T. Nichols ,  N. Conway  (on outreach),  A. Raymond ,  G. Fitzpatrick ,  M. Johnson  (on technical siting) to the formation of the HPC working group, which in turn built on the already long-running BHI Foundations seminar (with many thanks e. g. , to  F. Azhar ,  M. Lesourd ,  E. Curiel  and the participants of that seminar). In framing the scope of the still-developing Siting focus group that will report in subsequent publications, the Siting Workshop conveners and framers, including  A. Thresher  and  P. Natarajan  (later joined by  D. Palumbo ), thank the presenters at the first Siting Workshop which has helped guide subsequent developments:  C. Prescod-Weinstein ,  K. Kamelamela ,  H. Nielson ,  M. Johnson ,  K.
Using AI-based voice spoofing software, the criminals successfully impersonated the head of the firm's parent company, deceiving the CEO into believing he was speaking with his boss. The cybersecurity organization Symantec has stated that it encountered at least three examples of deepfake-based fraud in 2019, resulting in millions of dollars being lost  (Zakrzewski, 2019). Moreover, consumers are susceptible to blackmail, intimidation, sabotage, harassment, defamation, revenge porn, identity theft, and bullying  (Chesney & Citron, 2019; Cross, 2022; Europol, 2022; Fido et al. , 2022; Karasavva & Noorbhai, 2021; Whittaker et al. , 2020 ). Yet at the same time, this emerging technology also carries positive potential through different forms of commercialization  (Johnson & Diakopoulos, 2021; Maksutov et al.
Data collection and screening (Phase II) To identify relevant literature, we used three academic databases: Web of Science (WoS), ACM Digital Library, and IEEE Xplore. As a generic database, WoS is the most comprehensive, containing over 12,000 high-impact journals and scientific articles from over 3,300 publishers. The ACM Digital Library and IEEE Xplore databases focus on technical disciplines. When combined, these three databases offer extensive and balanced coverage of the existing literature on deepfakes. We conducted detailed searches in each of the three databases. Given the nascent stage of deepfake research, we did not want to pre-limit the searches with highly specific keywords that could result in the omission of important papers. Rather, to identify a wide range of publications to illuminate deepfakes and their implications, we used only the keywords "deepfake*" and "deep fake*" (* denotes plural forms) and manually identified any associated papers.
Second, for papers present in multiple databases, we kept only one record per paper and excluded other ones. For example, the paper titled "Deepfake Portraits in Augmented Reality for Museum Exhibits" by Nathan Wynn, Kyle Johnsen, and Nick Gonzalez (2021) was present in both WoS and IEEE Explore. We kept one record for it and removed the other one. We also excluded papers with title/abstract/keywords indexed in English in the databases when the actual publication was in a language other than English. Finally, from this pool of publications, we selected those contributing to the aims of this study. Here, only publications useful in answering any of our three research questions were retained. The rest were discarded. We preferred articles with literature reviews or clear conceptual frameworks  (Torraco, 2016) , as these tend to summarize previous research rather than focusing on a specific aspect of the phenomenon.
We chose this "top-to-bottom" approach because of the interdisciplinary nature of the phenomenon, allowing us to capture succinct summaries from multiple fields  (Toronto & Remington, 2020; Torraco, 2016). In addition, we included empirical studies that clearly articulated implications for either consumers (users) or firms (organizations). Our final list included 74 publications (WoS: 42; ACM Digital Library: 14; IEEE Xplore: 18). The details of these papers-including source database, title, authors, publication outlet, publication year, addressed research questions, form(s) of deepfake addressed, and key findings-are available in the appendix (Supplementary material, Table  3 ). The 74 publications reviewed in the current study were published in 57 different outlets, indicating that the topic currently attracts the attention of diverse publication outlets and is highly multidisciplinary.
To this end, online tools are becoming available. For instance, Jevin West and Carl Bergstrom at the University of Washington have created a website called "Which Face Is Real" (https://www. whi chfaceisreal. com). All of the images on the site are either computergenerated from thispersondoesnotexist. com using the StyleGAN software or are actual photographs from the FFHQ dataset of Creative Commons and public domain images. By putting the real and fake photos side by side, the site helps people become more analytical of potentially false portraits. At an individual level, a variety of social ties-defined as the diversity of offline groups and contexts represented in one's online social networks (Torres et al. , 2018)-can help increase awareness of fake content. Additionally, the study indicates that increasing consumer awareness of fake content, such as deepfakes, has a beneficial effect on verification behavior and network trust  (Torres et al.
Limitations and suggestions for future research As with any research, our study has certain limitations. First, we only investigated scientific papers indexed in three specific databases (Web of Science, ACM Digital Library, and IEEE Xplore). Despite the depth and breadth they offer in terms of literature coverage, we have inevitably missed some valuable knowledge available in other databases. Second, we only focused on papers published in English, omitting knowledge available in other languages. Accordingly, any future research that widens this coverage to include such literature will enhance our knowledge base. Third, we chose the conceptual lens of marketplace deception to approach the deepfake phenomenon. However, there could be alternative conceptual and theoretical frameworks to increase our understanding of deepfakes, such as market orientation and innovation  (Atuahene-Gima, 1996)  and ethical marketing  (Chonko & Hunt, 1985).
(2019, June  14 ). NY State Senate Bill S5575B. NY State Senate. https://www. nysenate. gov/legislation/bills/2019/s5575/amendment/b. Tong, X. , Wang, L. , Pan, X. , & gya Wang, J. (2020). An overview of deepfake: The sword of damocles in AI. 2020  International Conference on Computer Vision, Image  and  Deep Learning  (CVIDL),  265-273. Toronto, C. E. , & Remington, R. (2020). A step-by-step guide to conducting an integrative review. Springer. Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human Resource Development Review, 15(4),  404-428. Torres,  R. , Gerhart ,  N. ,  & Negahban , A. (2018). Epistemology in the era of fake news: An exploration of information verification behaviors among social networking site users. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 49 (3),  78-97.
Given the above two alternatives, the overall empirical strategy of this paper is to examine mortality outcomes for 23 representative countries, comparing the dynamics of actual and legislated (and projected in the case of countries that have already adopted automatic indexation mechanisms) retirement ages. The aim of the exercise is to evaluate the CAR and CRR approaches for all of the countries in the study in light of what is required to attain schemes that are intergenerationally actuarially fair based on actual and projected data for the period 2000 to 2050. The analysis encompasses medium-and high-income countries with a diversity of actual pension architecture, including both financial and nonfinancial (DB and DC) schemes. To generate forecasts of retirement age by age, sex, and year, we estimate period and cohort survival curves from stochastic mortality models.
Mortality and pension age data The datasets used in this study comprise mortality data and full pension age data. Mortality data are obtained from the Human Mortality Database (2021) and consist of observed death counts, D x,t , and exposure-to-risk, E x,t , classified by age at death (x = 60,. , 95), year of death (t = 1960,. , 2018) and sex for 23 homogeneous national populations (countries or areas) in different regions of the world. Table  2  lists the countries considered in this study together with details about data availability in the defined historical "lookback window", set from 1960 (or the most distant year available) to 2018 (or the most recent year available). The pension age data include actual and forecasted standard retirement age by sex from 2000 to 2050 for 23 countries.
Acknowledgements The authors would like to express their gratitude to the editors and two anonymous referees for their careful review and insightful comments, which helped strengthen the quality of the paper. The authors are thankful for the suggestions and remarks from participants at the  Sixteen International Longevity Risk and Capital Markets Solutions Conference, Copenhagen  in August 2021. Jorge M. Bravo  was supported by  Portuguese National Science Funds  through  Fundacão para a Ciência e a Tecnologia , grant  UIDB/04152/2020 -Centro   de Investigacão em Gestão de Informacão (MagIC)  and grant  UIDB/00315/2020 -Instituto   Universitário de Lisboa (ISCTE-IUL) ,  Business Research Unit (BRU-IUL). Mercedes Ayuso  is grateful to the  Spanish Ministry of Science and Innovation  for funding received under grant  PID2019-105986GB-C21.
The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020).
Various contact-restricting policies (e. g. , stay-at-home recommendations, curfews, police hours, partial or complete lock-downs) were enacted, and citizens were advised to adhere to public health recommendations (e. g. , hand washing, face masks, and spatial distancing). It quickly became clear that behavioural science had a major role to play  10. On April 11th, a team of researchers launched a call for international collaboration in social and moral psychology. The initiative quickly gained momentum, gathering a consortium of over 250 academics worldwide. The aim of this project was to collect data from as many countries as possible to serve as a public good for the scientific community by allowing future research to draw on this broad database collected during this early phase of the COVID-19 pandemic.
The survey, developed by the initial team, was circulated among the national teams, who provided feedback, translated it into 32 languages, and disseminated it online. The project concluded with responses from a total of 51,404 participants from 69 countries, 77 samples, between April 22nd and June 3rd, 2020. A key goal of the project was to test the hypothesis that national identity predicts support for public health measures during the COVID-19 pandemic, which has since been confirmed  11, 12. In addition to collecting variables to test this hypothesis, we collected data on a variety of other social and moral constructs to make of our multi-country large-scale survey a rich resource for future research. The survey focused on the following areas: on a) COVID-19 beliefs and compliance behaviours (COVID-19 public health support, COVID-19 risk perception, COVID-19 conspiracy beliefs, and COVID-19 testing behaviour); b) identity and social attitudes (national identification, national narcissism, and social belonging); c) ideology (political ideology); d) health and well-being (subjective physical health, a wealth ladder ranking, and psychological well-being); e) moral beliefs and motivation (generosity, morality as cooperation, moral identity, and moral circle); f) personality traits and dispositions (open-mindedness, self-esteem, trait optimism, trait self-control, narcissism, and cognitive reflection); and g) demographic variables (i.
e. , sex, age, marital status, number of children, and employment status). Using this dataset, project team members have pre-registered a variety of secondary hypotheses (see icsmp-covid19. netlify. app/preregistration), several of which have already been published  [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23]. In this paper, we present the complete ICSMP datasets to facilitate its findability, accessibility, interoperability, and reuse (FAIR;  24, 25  ) and maximize its educational impact  [26] [27] [28]. Fig. 1  A world map visualizing the number of participants in each surveyed country. Note: This heat map shows the number of respondents from each country. The gray areas are the countries that are not covered by the data, and the colour scale shows the size of the sample in accordance with the scale on the lower left side.
Participants. A total of 51,404 individuals from 77 samples across 69 countries participated in our survey. The inclusion criteria were the following: being 18 years of age and older, and giving informed consent (although researchers were encouraged to, ideally, recruit representative samples regarding age and gender). Data were collected between April 22nd and June 3rd, 2020. Figure  1  displays where the data were collected, coloured according to national sample size. Figure  2  displays the proportion of respondents in relation to the full sample. Figure  3  shows when the data were collected in each country. 1, 2  show the number of participants, the mean proportion of non-missing 'valid' answers, and age. When multiple samples were collected within the same country, data were split into numbered subgroups (e.
g. , for Brazil, which has three samples, they were flagged as Brazil_1, Brazil_2 and Brazil_3). Note that in the tables above, we kept country subsamples separated to highlight they were collected by different teams, often using different sampling methodologies or languages, which impact their characteristics (e. g. , representativeness). For the most part, participants were recruited via professional survey research companies and were incentivised to participate. In countries that, to our knowledge, did not possess polling infrastructure  30  , incentivising participants was not feasible. To collect data in these countries, leaders of national teams relied on online   1, 2  show the number of participants, the mean proportion of non-missing 'valid' answers, and age. When multiple samples were collected within the same country, data were split into numbered subgroups (e.
Personality traits. Six constructs: open-mindedness  50  , self-esteem  51  , trait optimism  52  , trait self-control  53  , narcissism  54  , and cognitive reflection  55. Demographics. Six questions: age, number of children, employment status, marital status, gender, and urbanicity. Metadata and attention check. An attention check was used to mitigate negative impact on data quality from potential non-human responses and the likelihood of biasing data and subsequent analysis of low base-rate outcomes-such as endorsement of COVID-19 conspiracies. We collected typical questionnaire metadata (e. g. , start, record, and end dates, duration, and language). In addition, we created an internal participant ID, added ISO2 and ISO3 country codes, and sample representativeness. Translation. The survey instrument was drafted in English and translated into other languages using the standard forward-backward method (i.
Data cleaning. We received individual data files from each national team. To merge these raw data, minor modifications were introduced, which we delineate in this section. First, we renamed columns to match across data sets, reordered variables alphabetically, and standardised variable labels. Furthermore, all missing values and values denoting the absence of a response were converted to NAs (not available). When ambiguous date formats were found (e. g. , on start date, end date, and record date), we manually specified the correct format and standardised them. At the second stage, we introduced multiple modifications to clean the data for research. Some modifications were introduced to every national data set, while others were introduced to specific national data sets (both of which are thoroughly reported in the Data Records section).
To each national data set, we recoded the attention check (attcheck) into pass (1) or fail (0); standardised generosity items (generosity1-3), recoded CRT items into intuitive (2), correct (1), and incorrect (0); converted the number of children (children) into a variable with a fixed range from zero to ten or more; recoded all participants declaring being older than 100 years old as 100; and we excluded all duplicates (i. e. , in case multiple participants were recorded with identical inputs within a national database, only the first input was retained).
Data records All materials associated with the ICSMP COVID-19 project can be found on the project's repository (comprising five folders) hosted by the Open Science Framework (OSF, https://doi. org/10. 17605/osf. io/tfsza)  56, 57  We also provide a data-driven codebook detailing how each measure was collected-e. g. , listing variable names, variable labels, and label values (dt. codebook. xlsx; osf. io/ecva2). The IRB folder contains both the Internal Review Board Ethics application (ICSMP Kent Ethics application full. pdf; osf. io/xt9gr) and Ethics approval (ICSMP Kent Ethics approval. pdf; osf. io/ce638). The folder Sample Type & Representativeness includes the documentation for an internal survey conducted with national team leaders about the employed survey methodology for the data provided (Sample Type & Representativeness.
zip; osf. io/fj5xn). The folder Survey Instrument contains the initial English version of our survey instrument along with its Qualtrics. qsf for reproducibility (Survey Instrument. zip; osf. io/nf48q). In the sub-folder Translations, we archived all 32 translated survey instruments along with a report on the languages of conducted surveys per country (i. e. , several countries had their surveys in multiple languages per country; Country and language. xlsx; osf. io/wj7d2). Potential for future research. The data contains four measures of COVID-19 beliefs and compliance, 17 social and moral psychological constructs, and six sociodemographic characteristics, amounting to 27 socially-relevant variables. To quantify the potential of this dataset-and assuming a typical research paper uses between three to five key main constructs plus sociodemographics and controls-we calculated the number of combinations of 17 constructs, taken three, four, and five at a time, yielding a grand total of 9248 possible unique designs.