Persistent Identifier
|
doi:10.18710/6YMZLS |
Publication Date
|
2025-06-16 |
Title
| Does standardization matter? Evaluating the potential of the Common European Framework of Reference for Languages (CEFR) to foster labour market inclusion of immigrants (DISCEFRN): Vignette study dataset |
Author
| Schmaus, Miriam (Western Norway University of Applied Sciences) - ORCID: 0000-0001-8192-6953 |
Point of Contact
|
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Schmaus, Miriam (Western Norway University of Applied Sciences) |
Description
| This data contains the collected information of the survey experiment that was carried out within the DISCEFRN project (see metadata section Funding Information).
Within DISCEFRN, we combined web-scraped job vacancy data of the Norwegian labour market with a factorial survey experiment that exploits real-world variation in CEFR requirements within these ads (n vignette ratings= 10,495; n employers= 1,527) to examine whether fictitious applicants with a refugee background face less language-based discrimination on the individual level among employers who use standardized language requirements in their (real-world) ads compared to those that don’t. We thereby varied different applicant characteristics related to ethnic origin and to formal (CEFR certificate) and informal language indicators (e.g. spelling, argumentation, professional reference on unobservable relational skills) within vignettes and collected information on job-, firm- and employer characteristics (most notably attitudes towards different refugee groups) with standard survey items. This allowed us to assess whether CEFR requirements are primarily mitigating biased applicant evaluations that are related to language-based statistical/error discrimination (less relevance of informal language indicators), related to discrimination tastes (less relevance of group-related attitudes), or both.
This dataset contains all information on the survey experiment. It is a stand-alone dataset and contains all relevant data to re-produce associated publications (See metadata field on Publications) or be reused for other research interests. Yet, it can still be linked to additional DISCEFRN datasets, i.e. the web-scraped data set, that also holds information on those employers that did not participate in the survey experiment (https://doi.org/10.18710/K6WA0V). (2025-05-21) |
Subject
| Social Sciences |
Keyword
| Language Requirements (CEFR)
Survey Experiment
Hiring Discrimination
Immigration
Ethnic inequalities
Labour market integration
Language-based discrimination |
Related Publication
| Schmaus, M., Bugge, E., & Carlsen, C. H. (2025). Are standardized language requirements a useful tool to reduce ethnic hiring discrimination? Pairing web-scraped data with a factorial survey experiment. doi: 10.31219/osf.io/jth3u_v1 https://doi.org/10.31219/osf.io/jth3u_v1 |
Language
| English |
Producer
| Western Norway University of Applied Sciences (HVL) https://hvl.no/en/ |
Production Date
| 2025-02-01 |
Production Location
| Norway |
Contributor
| Data Collector : Schmaus, Miriam
Data Curator : Schmaus, Miriam
Data Manager : Schmaus, Miriam
Funder : Marie Skłodowska-Curie Actions (MSCA, Horizon Europe Actions); Postdoctoral fellowship project (Miriam Schmaus): Grant agreement ID: 101065566; DOI: 10.3030/101065566
Hosting Institution : HVL
Project Member : Cecilie Hamnes Carlsen
Project Member : Edit Bugge |
Funding Information
| The European Union's Marie Skłodowska-Curie Actions (MSCA, Horizon Europe Actions): 101065566 |
Distributor
| Western Norway University of Applied Sciences (HVL) https://dataverse.no/dataverse/hvl |
Depositor
| Schmaus, Miriam |
Deposit Date
| 2025-05-21 |
Time Period
| Start Date: 2024-01-01 ; End Date: 2024-12-31 |
Date of Collection
| Start Date: 2024-01-01 ; End Date: 2024-12-31 |
Data Type
| survey; experimental data |
Series
| DISCEFRN |
Software
| STATA, Version: 17 |
Related Dataset
| Miriam Schmaus, 2025, "Does standardization matter? Evaluating the potential of the Common European Framework of Reference for Languages (CEFR) to foster labour market inclusion of immigrants (DISCEFRN): Web-scraped dataset", https://doi.org/10.18710/K6WA0V |