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
In this study, we examine which role the size of the immigrant population plays in explaining immigrant derogation within and between European regions. We draw upon group threat- and intergroup contact theory to consider the following question: does a larger size of immigrant population increase perceived group threat and thereby lead to greater immigrant derogation? Or does it increase intergroup contact and thereby ameliorate immigrant derogation? We test the empirical adequacy of these alternative suggestions using regionalized European Social Survey 2002 and official data which will be analyzed by means of multilevel structural equation modeling. Within regions, our results confirm that perceived group threat increases subsequent immigrant derogation. Likewise, intergroup contact reduces perceived group threat and thereby amends such derogation of immigrants. Between regions, our findings show that a larger size of the immigrant population increases both greater perceived group threat and intergroup contact. At the same time, the effects of perceived group threat and intergroup contact on immigrant derogation resemble those found within regions. In sum, these results lend evidence to the generalizability of both group threat- and contact effects. Implications of these findings for future research are discussed.
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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it