National identification, perceived threat, and dehumanization as antecedents of negative attitudes toward immigrants in <scp>A</scp>ustralia and <scp>C</scp>anada
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 The interplay of nationalistic threat perceptions, dehumanizing beliefs and intergroup emotions, and anti‐immigrant sentiment is analyzed in a cross‐national context with Australian ( N = 124) and Canadian ( N = 126) samples. National identification was linked to negative attitudes toward immigrants indirectly, via perceptions of immigrants as being in threatening zero‐sum relationships with citizens. In turn, perceived zero‐sum threat was associated with dehumanizing beliefs and emotions about immigrants. Significant baseline differences in hostility were observed across the samples, but the relationships among the variables were not moderated by participants' nationality. The study contributes to the literature examining how negative emotions and attitudes may serve to legitimize intergroup competition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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