The Challenge of Confronting Ageism: Impressions of Targets and Bystanders Who Intervene
Bibliographic record
Abstract
Abstract Does confronting ageism come with a cost? Benevolent ageism is viewed as more appropriate than hostile ageism which may lead to negative consequences for individuals who confront it. We examined whether impression costs are mitigated or exacerbated by the style of confrontation (moderate or strong) and the person who confronts (the target or a bystander). Young and older participants read a vignette and rated the target, perpetrator and bystander on warmth, competence, and the acceptability of each character’s actions. Participants rated targets who confronted more negatively than bystanders who confronted, and preferred moderate over strong confrontation. In addition, participants thought the perpetrator would be less likely to exhibit prejudicial behaviors again if the older target confronted the action rather than the bystander. This demonstrates the challenge that older adults face; confronting results in a negative impression of them but may be more effective in preventing ageist actions in the future.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".