MétaCan
Menu
Back to cohort
Record W4324026834 · doi:10.1177/07334648231161937

Ageism against Older Adults: How do Intersecting Identities Influence Perceptions of Ageist Behaviors?

2023· article· en· W4324026834 on OpenAlexfundno aff
Hannah M. Gans, Michelle Horhota, Alison L. Chasteen

Bibliographic record

VenueJournal of Applied Gerontology · 2023
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrejudice (legal term)PerceptionPsychologyOlder peopleWhite (mutation)Identity (music)Social psychologyRace (biology)Developmental psychologyGerontologyGender studiesMedicineSociology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.350
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied GerontologySame topicAging and Gerontology ResearchFrench-language works237,207