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17 results for “cross-national”
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Wave 1 Questionnaires: Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia: EXTRACT: Identification with Europe and Home Country
<p>It is a well-established fact that forming a mature and coherent political identity is one developmental task in adolescence and young adulthood. However, given different degrees of commitment on the regional, national, and European level, the question remains whether young people’s identification varies among those spheres? Drawing on data from the European Catch-EyoU-project, it was the goal of this study to examine whether young people can be classified according to their identification toward their home country and Europe and how these types are associated with age, gender, country as well as political interest, tolerance, and political participation. The study is based on adolescents and young adults from the Czech Republic, Germany, Great Britain, Greece, Estonia, Italy, Portugal, and Sweden (<em>N </em>= 9,339; <em>M</em>age=19.62; 59.1% female). Cluster analysis revealed five types of young people’s identification with country and Europe which showed significant associations between group membership and tolerance, political interest, and participation. The implications of distinguishing types of identification and their associations with political outcomes are discussed.</p>
Comparison of Drug Prescribing Before and During the COVID-19 Pandemic - A Cross-national European Study. Pharmaceuticals Consumption data
<p>Data and code supporting the article:</p> <p><strong>Comparison of Drug Prescribing Before and During the COVID-19 Pandemic - A Cross-national European Study </strong></p> <p>Prescription data from January 2017 to March 2021 for the Czech Republic, Germany, Lithuania, Slovenia, Spain (Catalonia), Sweden, and the United Kingdom (Scotland).<br>Data include the codes of the Anatomical-Therapeutic-Chemical classification (ATC) and corresponding numbers of dispensed defined daily doses (DDDs) and packs, aggregated by country, month and ATC.</p> <p>For more information, see the accompanying document ReadMe.txt.</p>
CATCH-EyoU Processes in Youth's Construction of Active EU Citizenship Cross-national Wave 1 Questionnaires Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia - EXTRACT
<p>The dataset was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538 <a href="http://www.catcheyou.eu/">http://www.catcheyou.eu/</a>. </p> <p>The data set consists of:</p> <ul> <li>1 data file saved in .sav format</li> </ul> <p>“CATCH-EyoU Processes in Youth’s Construction of Active EU Citizenship Cross-national Wave 1 Questionnaires Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia - EXTRACT.sav”</p> <ul> <li>1 README file</li> </ul> <p>The file was generated through IBM SPSS software. Discrete missing values: 88, 99. The .sav file (SPSS) can be processed using “R” (library “foreign”): <a href="https://cran.r-project.orgv/">https://cran.r-project.org</a></p> <p>This dataset relates to following paper: </p> <p>Ekaterina Enchikova, Tiago Neves, Sam Mejias, Veronika Kalmus, Elvira Cicognani, Pedro Ferreira (2019) Civic and Political Participation of European Youth: fair measurement in different cultural and social contexts. Frontiers in Education.</p> <p>Data Set Contact Person: Ekaterina Enchikova [UP-CIIE]; mail: enchicova@gmail.com </p> <p>Data Set License: this data set is distributed under a Creative Commons Attribution (CC-BY) <a href="http://creativecommons.org/licenses">http://creativecommons.org/licenses</a></p> <p> </p>
LLMs Languages Least Moderated: Testing Cross-National Moderation in the context of the EU and the US Elections on Chatbots
<p>AI Forensics had <a href="https://aiforensics.org/work/bing-chat-elections">previously exposed</a> that Microsoft Copilot's answers to simple election-related questions contained factual errors 30% of the time. In collaboration with Nieuwsuur, we uncovered how chatbots can recommend and support the dissemination of disinformation as a campaign strategy. Following those investigations as well as a request for information from the European Commission, Microsoft and Google introduced “moderation layers" to their chatbots so that they refuse to answer election-related prompts.</p> <p><strong>This dataset was produced as part<span> of project "LLMs: Languages Least Moderated" at the 2024 Digital Methods Summer School and Data Sprint, which AI Forensics facilitated</span> to allow participants to evaluate and compare the effectiveness of these safeguards in different scenarios.</strong> In particular, we investigated the consistency with which electoral moderation was triggered, depending the language of the prompt and the electoral context.</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Wave 1 Questionnaires: Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia – EXTRACT_Political passivity
<p>This dataset contains the data underlying the following publication: Dahl, V., Amnå, E., Banaji, S., Landberg, M., Šerek, J., Ribeiro, N., ... & Zani, B. (2017). Apathy or alienation? Political passivity among youths across eight European Union countries.European Journal of Developmental Psychology, 1-18, https://doi.org/10.1080/17405629.2017.1404985.</p>
CATCH-EyoU: Meanings and Practices of Youth Participation and Cases of Successful Participation: Cross-national Ethnography Cases
<p>This data set contains data related to the ethnographic qualitative study (participant observations and in-depth interviews) of citizens active in youth citizenship organizations. The selected participants are active in supporting, communicating and engaging young people’s active participation in diverse and varied causes (the environment, anti-austerity protests, pro-European vote, voting at 16, anti-fees and cuts campaigns, rights around civic spaces and youth centers, employment and jobs-related campaigns, issues around race and religion, volunteering, refugees, local housing and education). The ethnographic study was performed in Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia. </p> <p>The data set consists of: (1) eight national textual reports of detailed observations (ethnographic field notes) of youth civic and political organizations/individual youth. The reports are in English and are fully anonymized and redacted. (2) 48 carefully redacted and ethically permissioned English language transcripts of qualitative interviews (6 interviews from each partner country) and (3) 160 carefully redacted and ethically permissioned English language transcripts of participant-observation field notes (20 A4 pages per country).</p> <p>The names of organisations and personal data of participants or employees have been strictly redacted and anonymized in order to protect participants’ privacy and comply with ethical requirements. Instead generic descriptors such as ‘National Students Organisation’ or ‘Local Municipal Youth Volunteer Centre’ are used throughout.</p> <p>The data can be reused by researchers who want to compare our data with similar data collected in different countries, to perform textual analysis (content analysis and/or data mining) on our data. </p>
CATCH-EyoU: Meanings and Practices of Youth Participation and Cases of Successful Participation: Cross-national Documentary Evidence of Youth Civic and Political Participation Initiatives
<p>The data set integrates documentary evidence of national youth civic and political participation initiatives in Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia. The evidence are represented as pamphlets, brochures, leaflets, newsletters, social media and websites, you tube videos, meme and vine campaigns. The participation initiatives are selected with a focus on initiatives used by national youth citizenship organizations for generating, supporting, communicating and engaging young people’s active participation in diverse and varied causes (the environment, voting at 16, anti-fees and cuts campaigns, rights around civic spaces and youth centers, employment and jobs-related campaigns, issues around race and religion, volunteering, refugees, local housing and education).</p> <p> </p> <p>The data set consists of: (1) a spreadsheet integrating data from all partner countries, and containing qualitative descriptions of activities and cataloguing associated materials of youth civic and political organizations; (2) a textual report containing exemplar images of publicly available online newsletters, minutes, reports and campaign materials from across the consortium (where feasible), copyright cleared and creative commons screenshots of websites, invitation letters, records of personal conversations with members of youth civic teams, quotes from researcher-conversations on social media or f-2-f with members of teams with names redacted.</p> <p>Personal data and all non-public data has been anonymized in order to protect participants’ privacy.</p> <p>The data can be re-used by researchers who want to compare our cross- European data with similar data collected in different countries, to perform textual analysis (content analysis and/or data mining) on our data. Also other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Wave 2 Questionnaires
<p>Abstract</p> <p>WP7 was designed to address questions concerning young Europeans’ EU citizenship, in particular to shed light on factors relevant in processes of construction of citizenship and their joint workings by way of the quantitative analysis of questionnaire data provided by adolescents and young adults in various situations of life across eight EU countries representing variations in, e.g., their economic situation/crisis, political conditions, and their history as EU member state.</p> <p>This work package (WP7) sets out to address open questions concerning factors associated with youth’s active EU citizenship. In particular, assumed (directions of) influences of relevant factors and their joint workings will be examined among adolescents and young adults in various situations of life, across different EU countries representing variations in, e.g., economic situation/crisis, political conditions, and history as an EU member state. This dataset presents the second wave of data collection. WP7 wave 2 data collections have been completed at all eight participating sites in winter 2017/18. The national data sets have been checked and processed including analyses of measurement quality. Finally, a longitudinal cross-national data set has been established which is ready for analyses and available to all Consortium members.</p> <p>The dataset contains more than 7400 questionnaires submitted to adolescents and young adults from Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia.</p> <p>The data can be reused by researchers who want to compare our data with similar data collected at other points in historical time as well as in other countries than the eight European ones included. Likewise, stakeholders may be interested in reanalyzing our data particularly with a focus on descriptive survey-type information of European citizenship among youth across Europe. Earlier research on these issues is far more restricted in terms of the substantive scope, namely concerning insights into identity and behavioral aspects of participation on the European level and relevant processes, as well as in terms of the cross-national dimension including a larger number of countries from different European regions.</p> <p>File specifics</p> <p>This final working dataset is a cleaned version of raw data. The cleaning procedure involved (1) removing participants who left the survey on first pages of the questionnaire; (2) removing participants with clearly unreliable responses (i.e. choosing the same response option through the questionnaire); (3) removing participants who indicated age under 14 or over 30 in both waves, or indicated age under 14 or over 30 in one wave and had a missing value on age in the other.</p> <p>Two filter variables based on participants’ age are present in the dataset:</p> <ul> <li>B_Filter_Age1 – selects participants who indicated age between 14-30 or did not indicate age at wave 2</li> <li>B_Filter_Age2 – selects participants who indicated age between 14-30 at wave 2</li> </ul> <p>Other technical variables refer to participants’ unique identification code (ID), country of data collection (Country), and cohort (Cohort; younger versus older). Please note that the cohort variable does not strictly refer to participants’ actual age, but it indicates whether he or she completed the questionnaire intended for adolescents (younger) or young adults (older).</p> <p>Data file is in a proprietary format (SPSS .sav format) but it can be opened through “R”, a free software environment for statistical computing and graphics, using different “R” libraries (such as “foreign”).</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Longitudinal (Wave 1 and 2) Questionnaires
<p>Abstract</p> <p>WP7 was designed to address questions concerning young Europeans’ EU citizenship, in particular to shed light on factors relevant in processes of construction of citizenship and their joint workings by way of the quantitative analysis of questionnaire data provided by adolescents and young adults in various situations of life across eight EU countries representing variations in, e.g., their economic situation/crisis, political conditions, and their history as EU member state.</p> <p>In the overall design of CATCH-EyoU, WP7 figures as a major link building on the initial theoretical work of WP2 by providing information that speaks to the assumptions based on the literature reviewed and the conceptual ideas developed at that point. Moreover, WP7 draws on results yielded by other work packages as far as available at a given stage of WP7 progress feeding into the construction of questionnaires, hypotheses to be tested, and interpretation of findings, respectively. The goal is to, in turn, contribute to an evidence-based finalization of WP2 conceptual efforts meant to integrate the empirical contributions of the different strands of CATCH-EyoU.</p> <p>At the core of WP7 is a longitudinal assessment using a two wave questionnaire data including a large sample of young people in all countries of the Consortium. After piloting instruments, the first wave of data collection took place in winter 2016/17. Questionnaires, details of the procedure, sample characteristics, and results of preliminary cross-sectional analyses were documented in D7.2 (Findings of wave1: A cross-national report. Noack, Macek 2017). A first set of substantive WP7 wave 1 findings have been presented in a special issue of the European Journal of Developmental Psychology (<a href="https://www.tandfonline.com/toc/pedp20/15/3">Volume 15, 2018 - Issue 3</a>; <a href="https://www.tandfonline.com/doi/full/10.1080/17405629.2017.1391087">Being both – A European and a national citizen? Comparing young people’s identification with Europe and their home country across eight European countrie</a>s. Landberg et.al 2017) as well as in various presentations addressing scientific and broader public audiences. The major reason for establishing a longitudinal data set is the study of processes of the development of major aspects of EU citizenship among youth which entails analyzing the influence of factors such as individual characteristics or conditions met in the family and in school on, e.g., young people’s identification with Europe and political participation. This implies to run analyses that capture the direction of effects as postulated on theoretical grounds which is not possible with a cross-sectional data set but requires sophisticated analyses of longitudinal data.</p> <p>The dataset contains more than 12600 questionnaires submitted to adolescents and young adults from Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia.</p> <p>The data can be reused by researchers who want to compare our data with similar data focusing on other aspects of attitudinal and identity development in youths. Likewise, stakeholders may be interested in reanalyzing our data particularly with a focus on descriptive survey-type information on the development of European citizenship in adolescence and early adulthood.</p> <p>File specifics</p> <p>This final working dataset is a cleaned version of raw data. The cleaning procedure involved (1) removing participants who left the survey on first pages of the questionnaire; (2) removing participants with clearly unreliable responses (i.e. choosing the same response option through the questionnaire); (3) removing participants who indicated age under 14 or over 30 in both waves, or indicated age under 14 or over 30 in one wave and had a missing value on age in the other.</p> <p>Three general filter variables based on participants’ age are present in the dataset:</p> <ul> <li>Fltr_age1 – selects participants who indicated age between 14-30 at least in one wave (i.e. filters out all participants with unknown age)</li> <li>Fltr_age2 – selects participants who never indicated age beyond 14-30 (the age might be unknown)</li> <li>Fltr_age3 – selects participants who indicated age between 14-30 at least in one wave and never indicated age beyond 14-30</li> </ul> <p>The last filter variable is the strictest one (it combines the previous two) and it is recommended for use if it is essential that only people from the given age group are included in the analyses.</p> <p>Two additional filter variables based on participants’ age are provided for each wave (A_Filter_Age1, A_Filter_Age2, B_Filter_Age1, B_Filter_Age2). These filters can be used if data from wave 1 or wave 2 are analyzed separately.</p> <p>There are four general variables in the dataset: participants’ unique identification code (ID), country of data collection (Country), participant’s attendance in the study (Attn; indicating his or her participation in wave 1 only, wave 2 only, or both waves), and cohort (Cohort; younger versus older). Please note that the cohort variable does not strictly refer to participants’ actual age, but it indicates whether he or she completed the questionnaire intended for adolescents (younger) or young adults (older).</p> <p>Names of variables from wave 1 start with letter “A_”, while names of variables from wave 2 start with letter “B_”.</p> <p>Data file is in a proprietary format (SPSS .sav format) but it can be opened through “R”, a free software environment for statistical computing and graphics, using different “R” libraries (such as “foreign”).</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Wave 1 Questionnaires: Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia
<p>Abstract</p> <p>This work package (WP7) sets out to address open questions concerning factors associated with youth’s active EU citizenship. In particular, assumed (directions of) influences of relevant factors and their joint workings will be examined among adolescents and young adults in various situations of life, across different EU countries representing variations in, e.g., economic situation/crisis, political conditions, and history as an EU member state. This dataset presents the first wave of data collection. All teams collected data from a quite diverse sample of young people from their respective country.</p> <p>We achieved the targeted sample sizes due to our improved recruitment strategies (based on our experiences from the pilot assessment). More precisely, we could attract more than 10,400 young people to participate in our study (concrete numbers depend on sample selection). Since we initially set out to reach at least 6,400 young people, we were quite successful in our recruitment. Paper-and pencil as well as online modes of assessment proved to be equally effective.</p> <p>The data set integrates data resulting from the first submission wave (wave 1) of Catch-EyoU Questionnaire. The questionnaire was submitted to adolescents and young adults from Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia.</p> <p>Catch-EyoU Questionnaire was focused on attitudinal, identity, and behavioral aspects of European citizenship, on youth engagement and participation on the regional and national levels as well as on fostering and limiting conditions affecting these. Earlier research is far more restricted in terms of insights into identity and behavioral aspects of participation on the European level and relevant processes, as well as in terms of cross-national comparisons based on a substantial number of countries from different European regions.</p> <p>The data can be reused by researchers who want to compare our data with similar data collected at other points in historical time as well as in other countries than the eight European ones included. Likewise, stakeholders may be interested in reanalyzing our data particularly with a focus on descriptive survey-type information of European citizenship among youth across Europe.</p> <p>File specifics</p> <p>This final working dataset is a cleaned version of raw data. The cleaning procedure involved (1) removing participants who left the survey on first pages of the questionnaire; (2) removing participants with clearly unreliable responses (i.e. choosing the same response option through the questionnaire); (3) removing participants who indicated age under 14 or over 30 in both waves, or indicated age under 14 or over 30 in one wave and had a missing value on age in the other.</p> <p>Two filter variables based on participants’ age are present in the dataset:</p> <ul> <li>A_Filter_Age1 – selects participants who indicated age between 14-30 or did not indicate age at wave 1</li> <li>A_Filter_Age2 – selects participants who indicated age between 14-30 at wave 1</li> </ul> <p>Other technical variables refer to participants’ unique identification code (ID), country of data collection (Country), and cohort (Cohort; younger versus older). Please note that the cohort variable does not strictly refer to participants’ actual age, but it indicates whether he or she completed the questionnaire intended for adolescents (younger) or young adults (older).</p> <p>Data file is in a proprietary format (SPSS .sav format) but it can be opened through “R”, a free software environment for statistical computing and graphics, using different “R” libraries (such as “foreign”).</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Pilot Questionnaires
<p>Abstract</p> <p>This final working dataset is a cleaned version of raw data from our pilot study. The cleaning procedure involved (1) removing participants who left the survey on first pages of the questionnaire; (2) removing participants with clearly unreliable responses (i.e. choosing the same response option through the questionnaire); (3) removing participants who indicated age under 14 or over 30.</p> <p>The data set integrates the data resulting from 1390 Catch-EyoU Pilot Questionnaires submitted to adolescents and young adults from Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia.</p> <p>The purpose of creating this cross-national data set is to test and compare the quality of items and scales across countries. Given the nature of items and scales a comparable data base does not exist elsewhere.</p> <p>The data can be reused by researchers who want to run more in-depth analyses of the items and scales as well as to a limited extent for substantive analyses.</p> <p>File specifics</p> <p>Technical variables refer to participants’ unique identification code (ID), country of data collection (Country), cohort (Cohort; younger versus older), age group computed based on participants’ age (Agegroup_computed), type of assessment (Assess; paper versus online), and questionnaire version (Version; items were ordered differently between versions A and B). Please note that the cohort variable does not strictly refer to participants’ actual age, but it indicates whether he or she completed the questionnaire intended for adolescents (younger) or young adults (older).</p> <p>Data file is in a proprietary format (SPSS .sav format) but it can be opened through “R”, a free software environment for statistical computing and graphics, using different “R” libraries (such as “foreign”).</p>
CATCH-EyoU: D3.1 Policy Analysis: Cross-National Reports
<p>Abstract</p> <p>The data set includes data from the analysis of written public documents on youth policies produced at European, national and local level during a three years period between 2012-2014.</p> <p>The policy analysis aims at identifying dominant institutional policy discourses subsumed at European level and within eight EU countries: Sweden, Italy, Germany, Czech Republic, Portugal, United Kingdom, Estonia, and Greece.</p> <p>The data sets include full citation of data sources of policy documents and data resulting from the content analysis performed on the policy documents.</p> <p>The policy analysis reinvigorates the existing research conducted in this area (cf. Bee, Guerrina, 2014) by exploring youth policies and policy responses in the context of a contemporary political and social climate where European identity is deeply contested, and where the global migration effects of regional conflicts have also challenged understandings of and claims to European citizenship.</p> <p>The data can be reused by researchers who want to compare our data with similar data collected in different countries. Also, other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
CATCH-EyoU WP3: D3.2 Perspectives of Policy Makers on EU and on Youth Active Citizenship: a Cross-National Report
<p>Abstract</p> <p>The data set includes data from the analysis of semi-structured interviews collected with politicians, public officials and representatives of youth umbrella organizations at national and regional/local level.</p> <p>The aim of the interviews is to explore policy makers’ views on whether and to what extent European Youth policies have been implemented at national, regional and local levels in various member states. Moreover, policy makers are asked to identify actual and future challenges in the field of youth policies. Previous research has only partially answered to these questions; moreover, comparing different policy makers’ perspectives allows researchers to identify tensions and contradictions in policies implementation, providing new insight for improving policy implementation.</p> <p>The data can be reused by researchers who want to compare our data with similar data collected in different countries. Also, other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
CATCH-EyoU: Representation of the EU and Youth Active Citizenship in Educational Contexts: Cross-national Textbook Analysis
<p>The data set contains the results of the quantitative and qualitative content analysis of local textbooks from different subjects (e.g. ESL, EFL, History, Social Sciences, Civic Education) at ISCED 3 level (upper secondary schools as well as vocational schools). Data collection was carried out using a specifically designed analytical grid (Ribeiro; Ferreira & Menezes, 2016). The grid was tested and applied by national research teams (Portugal, Czechia, Estonia, Germany, Italy and Sweden) participating to Catch-EyoU project – each textbook analysis implied filling one grid. In total, 34 textbooks were analysed across the participating countries. All grids include excerpts of the textbooks (text or images, whenever legally possible). Quantitative analysis data and bibliographical metadata are also included.</p> <p>Data collection and analysis was aimed at getting an overall picture of school texts, including the analysis of number of paragraphs, pages and exercises about topics such as the EU, active citizenship, intercultural awareness, political involvement.</p> <p>Although textbook analysis is relatively common and there are other European projects that include it, the data analysis grid is original (and relatively innovative in the area) as it directly relates to the project topics.</p> <p>The potential users can be other researchers who might be interested not only in the grid but also in the analysis itself, either to use it with other textbooks or compare it with existing research or with similar data collected in different countries; teachers might also find it useful to explore the analysis as a basis for their practice. Also other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
How is ICT use linked to household transport expenditure? A cross-national macro analysis of the influence of home broadband access
<p>Dataset used for analysis in the paper.</p> <p>ABSTRACT: Understanding of the interactions between Information and Communication Technologies (ICT) and physical mobility is a major area of research with practical applications in a number of fields. Very little, however, is known regarding how these relationships vary on a cross-national basis, including across countries at different stages in development. To address this gap, this paper presents an analysis of household transport expenditure as a function of the available variables, with a particular focus on the ICT. This analysis is based on a cross-sectional dataset from 2010 comprising information on 33 countries including average household transport expenditure, ICT represented by the percentage of households with Internet access at home, and a number of contextual macroeconomic and infrastructural variables<br> Using a log-log framework we find that, in our sample of countries, household transport expenditure is negatively associated with Internet penetration with an elasticity of -0.394. We verify this to be robust to endogeneity using presence of restrictions on foreign ownership in the Internet market as an instrumental variable. We also control for potential differences in data quality across countries using the Corruption Perceptions Index. To the best of our knowledge, this is the first attempt to quantify this relationship at a cross-national level while also controlling for endogeneity and data quality issues. Among the control variables, we observe the estimated effects to be intuitive, and consistent with existing research and microeconomic understandings of the behaviour of individuals and households.</p>
Health Behaviors in School-age Children: A World Health Organization Cross-National Study
ClinicalTrials.gov study NCT00341510. IPD Sharing: Not stated. Countries: 1. Publications: 1.
How is ICT use linked to household transport expenditure? A cross-national macro analysis of the influence of home broadband access
<p>Dataset used for analysis in the paper.</p> <p>ABSTRACT: Understanding of the interactions between Information and Communication Technologies (ICT) and physical mobility is a major area of research with practical applications in a number of fields. Very little, however, is known regarding how these relationships vary on a cross-national basis, including across countries at different stages in development. To address this gap, this paper presents an analysis of household transport expenditure as a function of the available variables, with a particular focus on the ICT. This analysis is based on a cross-sectional dataset from 2010 comprising information on 33 countries including average household transport expenditure, ICT represented by the percentage of households with Internet access at home, and a number of contextual macroeconomic and infrastructural variables<br> Using a log-log framework we find that, in our sample of countries, household transport expenditure is negatively associated with Internet penetration with an elasticity of -0.394. We verify this to be robust to endogeneity using presence of restrictions on foreign ownership in the Internet market as an instrumental variable. We also control for potential differences in data quality across countries using the Corruption Perceptions Index. To the best of our knowledge, this is the first attempt to quantify this relationship at a cross-national level while also controlling for endogeneity and data quality issues. Among the control variables, we observe the estimated effects to be intuitive, and consistent with existing research and microeconomic understandings of the behaviour of individuals and households.</p> <p> </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.