Authoritarianism, Conservatism, Racial Diversity Threat, and the State Distribution of Hate Groups
Bibliographic record
Abstract
On the basis of K. Stenner's (2005) authoritarian dynamic theory, the author hypothesized that there is an interaction between U.S. state conservatism-liberalism and state racial heterogeneity threat, such that greater diversity threat tends to be associated with more hate groups in more conservative states and fewer hate groups in more liberal states. State aggregates of the conservative-liberal ideological preferences of 141,798 participants from 122 CBS News/New York Times national telephone polls conducted between 1976 and 1988 (R. S. Erikson, G. C. Wright, & J. P. McIver, 1993) served as proxies for authoritarian-nonauthoritarian dispositions. For the 47 states with complete data, the hypothesized interaction was tested for 2000, 2005, and 2006 with hierarchical multiple regression strategies and supported. The author's hypothesis was also affirmed with SES and the interaction of SES and diversity threat controlled for. In contrast, SES entirely accounted for simple relationships between threat and hate group frequency.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".