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Record W2012646296 · doi:10.2190/81xb-qpyn-9adu-5l11

Age-Related Health Stereotypes and Illusory Correlation

2004· article· en· W2012646296 on OpenAlexaff
Scott F. Madey, Alison L. Chasteen

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of Toronto
FundersNational Institute on Aging
KeywordsAffect (linguistics)PsychologyOlder peopleCompliance (psychology)GerontologyClinical psychologyDevelopmental psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

This experiment investigated how age-related health stereotypes affect people's judgments of younger and older patients' medical compliance. Previous research has shown that stereotypes of young adults include healthy components, but stereotypes of older adults include both healthy and unhealthy components (Hummert, 1990). We predicted that younger patients in poor health would violate people's expectations about health in younger individuals. As a result of this violation, people would perceive younger patients to be more non-cooperative than older patients. On the other hand, because people's stereotypes of older patients contain both good and poor health components, non-cooperative older patients would be no more memorable than cooperative older patients. These hypotheses were supported by data showing that both younger and older participants formed illusory correlations between younger patients and non-cooperative behavior, but not between older patients and non-cooperative behavior. Implications for how age-related health stereotypes might affect beliefs about compliance and healthcare policy are discussed.

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 score0.816
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.354
Teacher spread0.319 · 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

Citations8
Published2004
Admission routes1
Has abstractyes

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