2022 Swiss-German Adult Survey: Exploring Social Movements, Attitudes, Wealth Distribution, Gender Dynamics, Environmental Concerns, Language, Stereotypes, and Body Image

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Dataset Overview

Dataset title

2022 Swiss-German Adult Survey: Exploring Social Movements, Attitudes, Wealth Distribution, Gender Dynamics, Environmental Concerns, Language, Stereotypes, and Body Image

Canonical DOI

Used to cite the entire dataset, regardless of version updates.

https://doi.org/10.48573/v2ar-y980

DOI

Used to cite a specific dataset version.

https://doi.org/10.48573/681p-2556

Dataset description language

English

Data URL

-

Data Availability

-

Dataset Description

The data was collected in German and contains data from 1'094 people.

Remarks about the documentation

To identify the survey questions accurately, please start by reviewing the questionnaire (only available in German). This document reflects the questionnaire's structure and should be referenced to describe the survey. Additional codebooks are provided in both German and English. For specific details on experimental designs, filters, and the exact question framing, please refer to the German version of the codebook. Note that the variables' order in the codebook and datasets may slightly differ from the original questionnaire version, which is the one that participants saw. To establish the accurate question order and structure, rely on the questionnaire itself.

Version number

1.0

Legacy dataset version number

1.0.1

Embargo end date

-

Publication date

16.05.2024

Version notes

The authors' order was not reflecting the authors' contributions (i.e., there was a mistake in the initial submission).

Bibliographical citation

Eisner, L., Frisch, L. K., Hässler, T., Primoceri, P., Sebben, S., Tobias, R., Villiger, D., & Ullrich, J. (2024). 2022 Swiss-German Adult Survey: Exploring Social Movements, Attitudes, Wealth Distribution, Gender Dynamics, Environmental Concerns, Language, Stereotypes, and Body Image (Version 1.0.1) [Data set]. FORS. https://doi.org/10.48573/681p-2556

DIP MD5 hash

a2691b282836ade372de4bac140cad87

Dataset contents

/
metadata.yaml