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- Creator:
- Eby, David W and Molnar, Lisa J
- Description:
- Data are contained in an Excel spreadsheet formatted such that each row is a separate participant and each column is a separate question. This file is called: EbyEtAl-TransportCaregiver. A data dictionary that gives the text for each question and the response categories mappings is contained in another Excel Spreadsheet. This file is called: EbyEtAl-TransportCaregiverDictionary. The text of the survey, the development of weights, and response rate calculations can be found in the Deep Blue report discussed previously.
- Keyword:
- Caregiver Burden, Driving, and Automobile
- Discipline:
- Social Sciences
-
- Creator:
- Benjamin Leffel
- Description:
- The three datasets provided here identify the city location of all CDM projects in China by referencing the individual Project Description Documents (via the UNFCCC) attached to each project. Through this method, all 3,764 Clean Development Mechanism projects at the city-level in China are identified out of a total of over 8,000 globally.
- Keyword:
- climate finance, carbon offset, China, urban, clean development mechanism, cities, and climate change
- Citation to related publication:
- https://escholarship.org/uc/item/3vr8850s and https://doi.org/10.1002/wcc.709
- Discipline:
- Government, Politics and Law, Social Sciences, International Studies, and Business
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- Creator:
- Benjamin Leffel
- Description:
- Time series dataset of adoption by year of climate action plans by 177 U.S. cities, 2010-2019, with links to plans included. This dataset is intended for use by researchers and practitioners investigating both individual climate action plans and time series patterns of adoption at the municipal level.
- Keyword:
- climate change, climate action plan, municipal, and Urban Sustainability Research Group
- Discipline:
- Social Sciences and Government, Politics and Law
-
- Creator:
- Benjamin Leffel
- Description:
- Data were gathered to test three hypotheses on the impact economic growth has on environmental conditions in urban areas. The three hypotheses are: 1. Income will be associated with reductions in PM2.5, PM10, NO2 and SO2. 2. Public Administration GVA will be associated with reductions in PM2.5, PM10, NO2 and SO2. 3. Urban density will be associated with reductions in PM2.5, PM10, NO2 and SO2. More information about the research and the data can be found in: Benjamin Leffel, Nikki Tavasoli, Brantley Liddle, Kent Henderson & Sabrina Kiernan (2021) Metropolitan air pollution abatement and industrial growth: Global urban panel analysis of PM10, PM2.5, NO2 and SO2, Environmental Sociology, DOI: 10.1080/23251042.2021.1975349.
- Keyword:
- global cities, environment, urban, air pollution, income, Urban Sustainability Research Group, and student-friendly
- Citation to related publication:
- Benjamin Leffel, Nikki Tavasoli, Brantley Liddle, Kent Henderson & Sabrina Kiernan (2021) Metropolitan air pollution abatement and industrial growth: Global urban panel analysis of PM10, PM2.5, NO2 and SO2, Environmental Sociology, DOI: 10.1080/23251042.2021.1975349
- Discipline:
- Social Sciences
-
- Creator:
- Samuel, Sara M, Wilson, Diane L, and Fleming, Emily K
- Description:
- The International Committee of Medical Journal Editors (ICMJE) requires researchers to post individual participant data (IPD) plans for interventional clinical trials with registration in order to be eligible for publication in its member journals. This study looked at how researchers interpret the ICMJE requirements and the related prompts for information used by ClinicalTrials.gov. This data consists of the analyzed contents of the IPD plans that researchers at the University of Michigan (U-M) submitted with trial registrations for the first 27 months that the 2019 requirement was in effect.
- Keyword:
- research data sharing, research data policy, research data, clinical trials, ClinicalTrials.gov, individual participant data, IPD, data sharing plan, and compliance
- Citation to related publication:
- Samuel, S. M. & Wilson, D. L. & Fleming, E., (2023) “Evaluating individual participant data plans for ICMJE compliance: A case study at University of Michigan”, Journal of the Society for Clinical Data Management 3(4). doi: https://doi.org/10.47912/jscdm.257
- Discipline:
- Health Sciences, Social Sciences, and General Information Sources
-
- Creator:
- Krupka, Erin
- Description:
- The survey data used in this project is from two larger overarching projects titled the Rice Preferences Study and the Black Student Success Study. The Rice Preferences Study began with a sample of 661 entering undergraduates matriculating in August of 2016. This was 66.7% of the entering class, randomly selected. Of that sample, 553 completed the study with an 83.7% response rate. Prior to coming to campus in fall 2016 Rice students were given a battery of incentivized preference measures including risk aversion, loss aversion, altruism, in-group favoritism, time discounting, competitiveness, and so on. Over the subsequent four years that group was tested with new and repeated measures, in two to four tests per year. As a basis for comparison, each year a smaller sample (between 112 And 148) was drawn from incoming classes and tested with the same instruments. The remaining students from the Class of 2020 who had never been tested were invited in March 2020 to complete the initial study (259 of 376 completed the study). In March 2020, as Rice University closed, the team joined together to build a COVID module for the long-term Rice panel, as well as the other members of the Class of 2020. A total of 670 participated in this wave (67.1% of the graduating class). The Black Student Success Study recruited samples from PVAMU and TAMU in 2017 and again in 2019. This study aimed at understanding the effects of stereotype threat on Black student success in two different university environments in Texas: PVAMU, a historically Black university with about 9,000 students, 65% female, and 83% Black; and TAMU, a large state university with about 70,000 students, 47% female and 3.7% Black. That study was ongoing in 2020 when COVID struck. A total of 880 subjects responded to the initial survey out of a total of 3,709 who were contacted. Black subjects were over-sampled at TAMU, and constituted 37% of the TAMU sample. Respondents completed a one-hour survey that included measures of identity, non-cognitive skills, stereotype-threat vulnerability, and controls for economic preferences (survey measures) and family background. They were paid $20 for completing the study. In March 2020 additional funding was awarded through NSF to expand and follow the Rice, TAMU and PVAMU panels, focusing on the impact of COVID-19.
- Keyword:
- Norms, Preferences, Social Identity, COVID-19
- Discipline:
- Social Sciences
-
- Creator:
- Carlson, Jake
- Description:
- This data set is my analysis of data management plans (DMPs) that were written by researchers at the University of Michigan for awards made between March 2020 and February 2021. I conducted this analysis to explore the potential utility of DMPs as a tool to aid data curators in understanding and working with the associated data set. Variables collected include: the types and formats of the expected data sets, information about the metadata and documentation to be generated, the anticipated methods for making the data set publicly available, references to Intellectual Property allowances or concerns, and the stated duration for preserving the data sets.
- Keyword:
- Data management plans, Data curation, Data sharing, and Content Analysis
- Citation to related publication:
- Carlson, J. (2023) Untapped Potential: A Critical Analysis of the Utility of Data Management Plans in Facilitating Data Sharing. Journal of Research Administration. Fall 2023. Forthcoming.
- Discipline:
- Social Sciences
-
- Creator:
- Xu, Ying and Bradford, Nora
- Description:
- The data was collected from a survey study using Qualtrics described above. The data are in .csv format along with a codebook also in .csv format.
- Keyword:
- social chatbot, perception, and artificial intelligence
- Discipline:
- Social Sciences
-
- Creator:
- Wellman, Michael P.
- Description:
- For each game: - file in JSON format with raw payoff data - text file with game-theoretic analysis results
- Discipline:
- Social Sciences
-
- Creator:
- de Oliveira, Stephanie and Nisbett, Richard E.
- Description:
- These studies assess the effect of social identity on judgement and are described in "Demographically diverse crowds are typically not much wiser than homogeneous crowds" (de Oliveira, S., & Nisbett, R. E. Proceedings of the National Academy of Sciences, 2018) and the article’s Supporting Information appendix. Some studies use a variety of questions to assess multiple social identity factors; the other studies are narrowed to particular social identity variables. Each study includes some type of estimation or prediction task, collects social identity variables, and asks participants to indicate their answer strategies. Study 1 is a trivia and prediction task based on football team fan identity. Study 2 reports on demographics plus political and religious identity and asks participants to predict vote percentages in presidential primaries. Study 3 participants estimate the percentage of Americans that support statements on various polarizing political views and give likelihood ratings for presidential candidates to win the Iowa caucus; a variety of identity questions are asked including political and religious identity. Study 4 includes demographics plus political and religious identity questions and asks participants to predict how the candidates would perform in the 2016 United States presidential election. Study 5 asks participants to guess the popularity rating of books that had either gender-specific or gender-neutral appeal, and also to rate their own interest in the books. Demographic-based social identity variables such as sex are included. Study 6 includes a wide variety of social identity variables and asks participants to estimate the likelihood of events occurring in the near future. Study 7 participants are from diverse national backgrounds and completed judgement tasks that predicted stock prices, Olympic performance, and news events outcomes. The data are generally interpretable when examined in conjunction with the target article. A new data file for Study 6 was uploaded on April 4, 2018 to include variables that were inadvertently left out of the original Study 6 file. A new data file for Study 7 was uploaded on April 6, 2018 to include variables that were inadvertently left out of the original Study 7 file. A codebook for this data set was added on April 6, 2018.
- Keyword:
- Judgment/Decision Making and Estimate aggregation
- Citation to related publication:
- Demographically diverse crowds are typically not much wiser than homogeneous crowds. Stephanie de Oliveira Richard E Nisbett Proceedings of the National Academy of Sciences of the United States of America vol. 115 issue 9 (2018) pp: 2066-2071. https://doi.org/10.1073/pnas.1717632115
- Discipline:
- Social Sciences
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