Young at Heart: How Subjective Age Influences Perceptions and Expectations of Older Adults
Bibliographic record
Abstract
Abstract A younger subjective age is often associated with positive health outcomes among adults over the age of 65. However, it is also possible that those who attempt to look or act younger than their chronological age may face backlash given this behavior is in violation of prescriptive stereotypes that serve to maintain hierarchical age group boundaries. The degree to which younger and middle-aged perceivers anticipate violations of prescriptive age stereotypes (i.e., that older adults should act their age) may predict negative evaluations of older adult targets who feel ‘younger than their years.’ The present work examined younger and middle-aged adults’ (N = 678; Mage = 35.8, SDage = 9.56) attitudes and evaluations regarding 65-year-old targets who varied by gender (man, woman) and felt age (65, 45, or 25). Participants also reported their expectations regarding older targets’ potential violation of succession-, consumption- and identity- related prescriptive age stereotypes. Expectations of prescriptive stereotype violation mediated the relationship between older targets’ younger felt age and participants’ ratings of targets’ warmth, competence, and interaction intentions. Specifically, targets who felt younger than their chronological age were expected to violate prescriptive stereotypes, which in turn decreased ratings of targets’ warmth and competence and lessened participants’ willingness to interact with targets. Our findings suggest that a younger subjective age may not always benefit older adults. Specifically, consistent with a Social Identity Threat perspective, younger perceivers’ concerns about preserving strict age group boundaries may explain discriminatory attitudes and evaluations of counter-stereotypical older adults.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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".