Communicating group norms through election results
Bibliographic record
Abstract
In a representative democracy, leaders (ideally) who are elected through the electorates should indicate consensus that the newly elected leader truly does represent the majority of the nation or the group. That is, once elected, can the ensuing perceptions of the electorate's consensus provide the newly elected leader with a sense of legitimacy and the ability to represent the group? Two experiments demonstrate that the perceptions of group consensus stemming from democratic elections can imbue newly elected leaders (even if they were once deviant) with legitimacy. Study 1 (N = 158) demonstrates that normative leaders are perceived as more legitimate than deviant leaders when elected with high voting consensus, which increased the perceived prototypicality of the normative leader through greater perceptions of legitimacy. Study 2 (N = 182) showed that newly elected leaders (vs. candidates) are perceived as more legitimate, which in turn, increases the group's perceptions of the once deviant leader's prototypicality, granted that the leader is democratically elected. Results suggest that democratic elections create conditions under which once deviant leaders can gain in perceived prototypicality and create lasting changes to the group identity.
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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 | 0.014 | 0.069 |
| 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 | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".