The social transmission of overconfidence.
Bibliographic record
Abstract
, which predicts that individuals calibrate their self-assessments in response to the confidence others display in their social group. Six studies that deploy a mix of correlational and experimental methods support this hypothesis. Evidence indicates that individuals randomly assigned to collaborate in laboratory dyads converged on levels of overconfidence about their own performance rankings. In a controlled experimental context, observing overconfident peers causally increased an individual's degree of bias. The transmission effect persisted over time and across task domains, elevating overconfidence even days after initial exposure. In addition, overconfidence spread across indirect social ties (person to person to person), and transmission operated outside of reported awareness. However, individuals showed a selective in-group bias; overconfidence was acquired only when displayed by a member of one's in-group (and not out-group), consistent with theoretical notions of selective learning bias. Combined, these results advance understanding of the social factors that underlie interindividual differences in overconfidence and suggest that social transmission processes may be in part responsible for why local confidence norms emerge in groups, teams, and organizations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".