“ACT YOUR AGE!” YOUNG ADULTS’ CONCERN REGARDING PRESCRIPTIVE AGE STEREOTYPE VIOLATION
Bibliographic record
Abstract
Abstract A younger subjective or ‘felt’ age is often associated with positive health outcomes among adults over 60. However, a dearth of research examines young adults’ attitudes towards older people who report feeling ‘young at heart’. The degree to which a young adult feels concerned about violations of prescriptive age stereotypes (i.e., that older people should act their age) may predict their reactions to older adults who feel young at heart. The present work examines young adults’ (N = 296) attitudes toward older vignette characters described as feeling either their age (65), 45, or 25. Participants evaluated one of six possible characters and completed a measure of their concern that the character would violate prescriptive age stereotypes (e.g., “I am concerned that older people like the person described in the vignette will come to places where I like to hang out.”). Participants were more concerned that characters who felt 25 or 45 would violate prescriptive age stereotypes compared to characters who felt 65. Moreover, concern about characters’ potential stereotype violation predicted participants’ attitudes toward the character. Specifically, the more concerned participants felt, the lower they rated characters’ competence, particularly when the character felt 25 or 65. These findings suggest that older adults’ felt ages and younger adults’ concerns about preserving strict age-group boundaries may be key predictors of evaluations of older people. To develop interventions to reduce ageism, more work must consider younger people’s reactions to older adults’ felt ages as well as their concern regarding prescriptive age stereotypes.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".