Ageism against Older Adults: How do Intersecting Identities Influence Perceptions of Ageist Behaviors?
Bibliographic record
Abstract
Most ageism research has focused on prejudice against older people without considering their multiple intersecting identities. We investigated perceptions of ageist acts that targeted older individuals with intersecting racial (Black/White) and gender identities (men/women). Both young (18-29) and older (65+) adult Americans evaluated the acceptability of a variety of instances of hostile and benevolent ageism. Replicating prior work, benevolent ageism was seen as more acceptable compared to hostile ageism, and young adults rated ageist acts as more acceptable than older adults. Small intersectional identity effects were observed such that young adult participants perceived older White men to be the most acceptable targets of hostile ageism. Our research suggests that ageism is viewed differently depending on the age of the perceiver and the type of behavior exhibited. These findings also suggest intersectional memberships should be considered, but further research is needed given the relatively small effect sizes.
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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 | 0.009 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".