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Face Adaptation and Attractiveness Aftereffects in 8-Year-Olds and Adults

2009· article· en· W2164350486 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChild Development · 2009
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsQueen's UniversityBrock UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyAdaptation (eye)AttractivenessDevelopmental psychologyPhysical attractivenessCognitive psychologyFace (sociological concept)PsychoanalysisNeuroscience

Abstract

fetched live from OpenAlex

A novel method was used to investigate developmental changes in face processing: attractiveness aftereffects. Consistent with the norm-based coding model, viewing consistently distorted faces shifts adults' attractiveness preferences toward the adapting stimuli. Thus, adults' attractiveness judgments are influenced by a continuously updated face prototype. To investigate the development of this process, a novel method was developed for 8-year-olds. After reading a storybook composed of faces with either compressed or expanded features, 8-year-olds' ratings of faces distorted in the direction of the adapting stimuli increased. Nonetheless, they required larger distortions than adults to rate undistorted faces as most attractive preadaptation. Thus, although 8-year-olds' attractiveness preferences are influenced by a continuously updated prototype, their face space is less refined than that of adults.

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.

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 score0.444
Threshold uncertainty score0.473

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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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