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- 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:
- Eckel, Catherine, Hoover, Hanna, Krupka, Erin, Sinha, Nishita, and Wilson, Rick
- Description:
- The research reported here is part of a larger study where we recruited students from the entering undergraduate classes in 2016, 2017, 2018 and 2019 at Rice University. The aim of the larger project is to examine the evolution of economic preferences (altruism, risk aversion, time preference, competitiveness, loss aversion, in-group favoritism, among others) across their college years. Subjects participated in numerous laboratory and online studies between matriculation and 2021. This paper uses data from the experimental design of a subset of tasks that subjects completed. The survey wave used in this paper was collected in June and July of 2021. This survey was composed of fifteen modules and had a total of 710 participants. and The survey consisted of 15 modules. Module 1 consisted of questions on COVID-19 related behavior and future expectations of the COVID-19 pandemic. Module 2 consisted of an emotion elicitation task. Module 3 solicited trust levels of several authorities and news outlets. Module 4 consisted of several general socioeconomic preference questions. Module 5 asked questions related to how frequently subjects provide various forms of help. Module 6 solicited social appropriateness ratings regarding COVID-19 preventative behavior. Module 7 consisted of an estimation task. Module 8 was the dictator game with the freshmen recipient. Module 9 involved a risky investment decision task. Module 10 was the dictator game with the same-class recipient. Module 11 involved a trust-game. Module 12 was the dictator game with charity as the recipient. Module 13 asked questions regarding help received by the university as well as COVID-19 academic impact. Module 14 included questions regarding the subjects’ COVID-19 infection status. Module 15 posed questions regarding subjects’ resiliency. Only modules 8, 10, and 12 were used in this analysis. These corresponded to Q11 - Q18 of the instrument. In each module, subjects played a dictator game, guessed what others did in the game and played a coordination game designed to elicit norms for the dictator game they just played. After the subject completed the survey, we randomly selected a module for payment. Subjects then received an email alerting the subject which module was selected for payment and how much money they would receive given their responses in the selection module. Data was analyzed using STATA; if running the do file for STATA, and not already installed, then add ""capture ssc install estout" to the very top of the .do file.
- Keyword:
- Dictator game, Social norms, and Charitable giving
- Discipline:
- Social Sciences
-
- Creator:
- Brennan, Jonathan R
- Description:
- These files contain the raw data and processing parameters to go with the paper "Hierarchical structure guides rapid linguistic predictions during naturalistic listening" by Jonathan R. Brennan and John T. Hale. These files include the stimulus (wav files), raw data (BrainVision format), data processing parameters (matlab), and variables used to align the stimuli with the EEG data and for the statistical analyses reported in the paper (csv spreadsheet). and Updates in Version 2: - data in BrainVision format - added information about data analysis - corrected prePROCessing information for S02
- Keyword:
- Linguistics, Speech, and EEG
- Citation to related publication:
- Brennan, J. R., & Hale, J. T. (2019). Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoS ONE 14(1). e0207741
- 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
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