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Record W2159570811 · doi:10.1093/geronb/gbs064

Friend or Foe? Age Moderates Time-Course Specific Responsiveness to Trustworthiness Cues

2012· article· en· W2159570811 on OpenAlexaff
Raluca Petrican, Tammy English, J. J. Gross, Morris Moscovitch

Bibliographic record

VenueThe Journals of Gerontology Series B · 2012
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsPsychologyGazeTrustworthinessCognitionCognitive psychologyPersonalityFacial expressionDevelopmental psychologySocial cueDynamics (music)PerceptionSocial psychologyNeuroscienceCommunication

Abstract

fetched live from OpenAlex

OBJECTIVES: There is growing evidence of a greater focus on positive relative to negative information in older adulthood. Up to date, the age-related positivity effect in affective processing has been only investigated with respect to explicit emotional cues. Thus, the purpose of this study was to investigate whether similar age-related differences would be observed in reference to subtler cues, such as emotionally suggestive structural facial characteristics. METHOD: We used a gaze following paradigm and investigated the temporal dynamics of responding to facial trustworthiness cues in younger and older adults. RESULTS: Both age groups provided similar trustworthiness evaluations. Nonetheless, under responding conditions that allowed for volitional modulatory influences (600 ms), older (but not younger) adults with superior cognitive resources showed more gaze following in response to trustworthy than to untrustworthy looking faces. CONCLUSIONS: This study provided initial evidence that the age-related positivity effect in affective processing extends to subtle emotional cues, generally interpreted as being reflective of socially relevant personality traits. Implications for aging theories of motivated cognition and developmental changes in reliance on superficial affective cues 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.151
GPT teacher head0.370
Teacher spread0.219 · 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 designBench or experimental
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

Citations29
Published2012
Admission routes1
Has abstractyes

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