“No Thanks, We're Full”: Individual Characteristics, National Context, and Changing Attitudes toward Immigration
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 paper we examine how individual-level characteristics and national context affect attitudes toward immigration. Although many previous studies have compared attitudes toward immigration across countries, little attention has been paid to how attitudes may be affected by changes within a country over time. We take advantage of seventeen national Canadian Gallup surveys to consider how differences in national economic conditions and changing immigration flows affect attitudes and changes in attitudes between 1975 and 2000. While the state of the national economy affects attitudes this is not the case for the rate of immigration. Rather than affecting some groups more than others the state of the economy has a relatively uniform effect across groups. Our results also show that far from being a continuum, being anti-immigration and being pro-immigration are qualitatively different. Interest, ideology, and the national economy affect anti-immigration sentiments, but only ideology affects pro-immigration sentiments.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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