The Moderating Role of Age-Group Identification and Perceived Threat on Stereotype Threat among Older Adults
Bibliographic record
Abstract
Although research has shown that older adults are negatively affected by aging stereotypes, relatively few studies have attempted to identify those older adults who may be especially susceptible to these effects. The current research takes steps toward identifying older adults most susceptible to the effects of stereotype threat and investigates the consequence of stereotype threat on the well-being of older adults. Older adults were tested on their recall of a prose passage under normal or stereotype threatening conditions. Memory decrements for those in the threat condition were moderated by perceived stereotype threat such that greater decrements were seen for those who reported greater perceived threat. A similar pattern was observed for negative emotion, such that those in the threat condition who reported higher perceptions of threat experienced a greater decrease in positive emotions. Age group identification also proved to be an important factor, with the strongly identified performing worse than the weakly identified. As well, high age-group identification buffered some of the negative affective consequences associated with stereotype threat, which is consistent with some models of coping with stigma.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".