Explaining time trends in public opinion: Attitudes towards immigration and immigrants
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
Why does public opinion change over time? Much debate on this question centers on whether it is caused by the replacement of people or by individuals changing how they think. Theoretical approaches to this question have emphasized the importance of birth cohort succession, generational differences, and changing macro-economic conditions. In this article, we consider the extent to which these processes can account for changing attitudes towards immigration and immigrants. We use a new approach to the study of time trends in public opinion to analyze over 20 years of data on attitudes in Canada. This approach uses multi-level analysis to split attitudinal change into its cohort and period components. We find that most attitude change is the result of changing macro-economic conditions. In contrast, birth cohort succession has little effect. While there is modest evidence of generational differences in attitudes, these differences do not comprise a major part of the overall trend.
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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 | 0.000 |
| 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