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
The research examines the extent to which attitudes toward foreigners vary across European countries. Using data from the European Social Survey for 21 countries the analysis reveals that foreigners' impact on society is viewed in most countries in negative rather in positive terms. The negative views are most pronounced with regard to foreigners' impact on crime and least pronounced with regard to foreigners' impact on culture. Multi-level regression analysis demonstrates that the negative views tend to be more pronounced among individuals who are socially and economically vulnerable and among individuals who hold conservative political ideologies. The analysis also reveals that negative attitudes toward foreigners tend to be more pronounced in countries characterized by large proportions of foreigners, where economic conditions are less prosperous, and where support for right-wing political parties is more prevalent. The analysis shows that inflated perception of the size of the foreign population is likely to increase negative views toward foreigners and to mediate the relations between actual size and attitudes toward foreigners' impact on society. The findings are presented and discussed in light of sociological theories on individuals and structural sources of public attitudes toward out-group populations and on the role of perceptions in shaping such attitudes.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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