The boundary within: Are applicants of Southern European descent discriminated against in Northern European job markets?
Bibliographic record
Abstract
Abstract In the aftermath of the Euro debt crisis, negative stereotypes about Southern Europeans were (re)activated across Northern European countries. Because these stereotypes make explicit reference to productivity-relevant traits, they have the potential to influence employers’ hiring decisions. We draw on a sub-sample of the Growth, Equal Opportunities, Migration and Markets discrimination study (GEMM) to investigate the responses of over 3500 firms based in Germany, the Netherlands and Norway to identical (fictitious) young applicants born to Greek, Spanish, Italian and native-born parents. Using French descendants as a placebo treatment and sub-Saharan African descendants as a benchmark treatment, we find severe levels of hiring discrimination against Southern European descendants in both Norway and the Netherlands, but not in Germany. Discrimination in Norway seems largely driven by employers’ preferences for applicants of native descent, while in the Netherlands discrimination seems specifically targeted against Greek and Spanish descendants. Dutch employers’ propensity to penalize these two groups seems driven by information deficits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".