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Record W4288384888 · doi:10.1037/pag0000702

Absence of a mere-exposure effect in older and younger adults.

2022· article· en· W4288384888 on OpenAlexfundno aff
Jason K. Chow, Stephen Rhodes, Nicholas O. Rule, Bradley R. Buchsbaum, Lynn Hasher

Bibliographic record

VenuePsychology and Aging · 2022
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPsychologyPsycINFOYoung adultDevelopmental psychologyAge groupsDemographyMEDLINE

Abstract

fetched live from OpenAlex

The mere-exposure effect, in which repeated stimuli are liked more than novel stimuli, is a well-known effect. However, little research has studied adult age differences in mere-exposure effects, despite possible applications in helping older adults transition to new living environments. Here, we report four experiments assessing mere-exposure to neutral-face stimuli in groups of older and younger adult participants tested online. In each experiment, repeated face exposure did not increase liking within either age group; rather, Bayesian evidence favored the null hypothesis of no effect. Older adults reported higher overall liking ratings relative to younger adults, and both groups preferred younger faces, though this tendency was stronger in the younger group. Further exploratory analysis considering factors such as gender or race of the faces and participants did not reveal any consistent results for the mere-exposure effect. We discuss these findings in relation to other recent studies reporting mixed evidence for mere-exposure effects. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.310
Teacher spread0.300 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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