How elections shape perceptions of ideal leadership.
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
= 200), surveyed eight times between October 2020 and January 2021, and reported their perceptions of the characteristics of the ideal leader. Results from a regression discontinuity in time and repeated measurement analyses found that the election altered two dimensions of the average U.S. leadership prototype. We specifically find participants' perceptions of Tyranny and Masculinity to decrease, that is, shifts to more Biden-like and less Trump-like leadership prototypes. Other dimensions of the leadership prototype remained stable, that is, charisma, sensitivity, dedication, intelligence, and dynamism. Analyses examined two boundary conditions of the effect: political identification and the acceptance of the election result as legitimate. Only perceived legitimacy was found to moderate the effect with the shift in leadership prototypes being driven by individuals who accepted the result of the election as legitimate. Our findings demonstrate the dynamic nature of leadership prototypes in response to real-world events and more broadly how an election can shape psychological perceptions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it