Ethnoreligious Identity, Immigration, and Redistribution
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
Abstract Do increasing, and increasingly diverse, immigration flows lead to declining support for redistributive policy? This concern is pervasive in the literatures on immigration, multiculturalism and redistribution, and in public debate as well. The literature is nevertheless unable to disentangle the degree to which welfare chauvinism is related to (a) immigrant status or (b) ethnic difference. This paper reports on results from a web-based experiment designed to shed light on this issue. Representative samples from the United States, Quebec, and the “Rest-of-Canada” responded to a vignette in which a hypothetical social assistance recipient was presented as some combination of immigrant or not, and Caucasian or not. Results from the randomized manipulation suggest that while ethnic difference matters to welfare attitudes, in these countries it is immigrant status that matters most. These findings are discussed in light of the politics of diversity and recognition, and the capacity of national policies to address inequalities.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.000 | 0.002 |
| 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