Does perceived labor market competition increase prejudice between refugees and their local hosts? Evidence from Uganda and Ethiopia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We study whether perceptions of labor market competition negatively influence out-group attitudes between refugees and their local hosts using a survey vignette experiment conducted in urban and rural Ethiopia and Uganda. Our vignette consists of a short story about a fictional job-seeker in which we randomize the citizenship (refugee/national) and occupation (same as/different from respondent). Our estimates suggest that host attitudes are significantly more negative when the vignette character is a refugee in the same occupation. Such prejudice against the out-group is not confirmed among refugees. Exploring the context-dependency of our results, evidence suggests that negative attitudes towards refugees that are tied to perceived labor market competition largely manifest in contexts of limited refugee worker presence. Hence, perceived labor market competition contributes to prejudicial attitudes, but results suggest that these perceived threats do not necessarily coincide with experienced labor market competition between refugees and their hosts. Additional heterogeneity analysis based on prior contact and ethno-linguistic proximity provides suggestive evidence that cross-group interactions reduce the salience of perceived labor market competition as a driver of out-group prejudice in refugee settings. • We study how perceived job competition influences outgroup attitudes in Ethiopia and Uganda. • Results show that perceived job competition links to negative attitudes toward refugees. • Heterogeneity analysis shows results are driven by hosts competing with few refugees. • Ethnolinguistic proximity and prior contact reduce negative attitudes toward refugees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it