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Record W2132659118 · doi:10.1093/geronb/gbr063

Age and Antiaging Technique Influence Reactions to Age Concealment

2011· article· en· W2132659118 on OpenAlexaff
Alison L. Chasteen, Nadia Bashir, Christina E. Gallucci, Anja Visekruna

Bibliographic record

VenueThe Journals of Gerontology Series B · 2011
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyAge discriminationMiddle ageYoung adultAge groupsDevelopmental psychologyOlder peopleAgeingGerontologyDemographyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Despite the rapid expansion of the antiaging cosmetic industry in recent years, little is known about the current social judgment consequences of concealing one's age. In two studies, we examined perceivers' evaluations and mental representations of individuals who engage in age concealment. METHODS: In Study 1, we assessed young and older adults' reactions toward a middle-aged or older adult target who engaged in mild or major forms of age concealment. In Study 2, we examined the social consequences of age concealment in greater detail by including younger middle-aged targets and expanding the range of concealment procedures used. RESULTS: Targets received less favorable evaluations (a) to the extent that they engaged in invasive procedures, (b) when they were viewed by young adults rather than by older adults, and to some degree, (c) if they were middle-aged adults rather than older adults. Participants held different expectations concerning aging and age concealment depending on the age of the target and the antiaging technique used. DISCUSSION: These findings suggest that reactions to age concealment vary according to the concealment technique used, the age of the perceiver, and to some extent, the age of the target.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.122
GPT teacher head0.388
Teacher spread0.267 · 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.

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

Citations21
Published2011
Admission routes1
Has abstractyes

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