Bibliographic record
Abstract
At a time, ‘American authoritarianism’ was considered an oxymoron; I argue that it has always been a national fairytale. Tracking increased ingroup-outgroup political affinity, antipathy, and affective polarization, this paper provides a scoping review of American authoritarianism since the late nineteenth century. I provide abbreviated cases analyses for the Reconstruction and Jim Crow authoritarian regimes, George Bush Jr.’s ‘War on Terror’, and Donald Trump’s 2016 presidency as authoritarianism personified. These cases underscore the growing propensity for authoritarianism in the post-Trump era. As a result, this research fills gaps in extant political and psychological scholarship, focusing on affinity, antipathy, and affective polarization in contemporary U.S. political culture. By using three elements of Adorno et al.’s (1950) nine-point scale to classify authoritarian personalities, this paper situates its analysis within Americans’ increasing submission to an acknowledged authority, aggression towards perceived outgroup members, and their belief in simple answers and polemics.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".