Abstract
Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.
Original language | English |
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Article number | 114 |
Number of pages | 27 |
Journal | Scientific Data |
Volume | 12 |
Issue number | 1 |
DOIs | |
Publication status | Published - 20 Jan 2025 |
Bibliographical note
Copyright © The Authors(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 InternationalLicense, which permits use, sharing, adaptation, distribution and reproduction in any medium or
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Data Access Statement
The TISP dataset, additional data, R code, pre-computed statistical models, additional materials and high-resolution versions of the figures presented in this article are available at the OSF: https://osf.io/5c3qd (see Data Records section)51. The datasets are ready to use with popular statistical software like R (recommended), IBM SPSS Statistics and Microsoft Excel.The OSF repository contains a wiki with information on the content of the folders and further instruction on how to use the files. The R code accompanying the datasets (folder 02_code) includes detailed annotations so that users can easily retrace and replicate the data-preprocessing procedures and validation analyses.
We developed a web-based data visualisation dashboard using R shiny97. Users may explore data on key variables of the TISP project across countries and subsamples. The dashboard is under development. It can be accessed at: https://tisp.shinyapps.io/TISP/.
All data as well as the R code, and pre-computed models underlying the analyses described in this article, and Figs. 1–4 in high resolution are available at the Open Science Framework: https://osf.io/5c3qd.
Keywords
- Attitude
- Climate Change
- Communication
- Cross-Sectional Studies
- Humans
- Public Opinion
- Science
- Surveys and Questionnaires
- Trust