Economic thinking and cultural enrichment beliefs about immigration: Development and validation of the ETCEI scale
Bibliographic record
Abstract
In Canada, political discourse on immigration is often framed in terms of (cultural and economic) contribution. Research on immigration attitudes, however, are primarily framed in terms of realistic and symbolic threat and competition. We develop a scale assessing Economic Thinking and Cultural Enrichment Beliefs About Immigration (ETCEI; Study 1-3) to reflect this contemporary discourse. Economic thinking was negatively associated with cultural enrichment beliefs––a pattern reflected in their association with ideological dispositions and personality (Study 1-2). Cultural enrichment beliefs were associated with ideological dispositions and traits associated with pro-diversity orientations, predicting preferences for expanding immigration and positive attitudes towards non-White European groups. Economic thinking was associated with prejudice-related ideological dispositions and individual differences, preferences towards economic migrants, East Asians (Study 2). Looking at measurement invariance and group differences (Study 3), immigrants and men scored higher on economic thinking; women and racialized people scored higher on cultural enrichment beliefs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".