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Record W2008814757 · doi:10.1080/0361073x.2013.839307

Perceived Duration of Emotional Events: Evidence for a Positivity Effect in Older Adults

2013· article· en· W2008814757 on OpenAlexaff
Jeffrey R. Nicol, Jessica Tanner, Kelly Clarke

Bibliographic record

VenueExperimental Aging Research · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsNipissing University
Fundersnot available
KeywordsSocioemotional selectivity theoryPsychologyArousalAffect (linguistics)Time perceptionPerceptionContext (archaeology)Developmental psychologyYoung adultFacial expressionDuration (music)Emotion perceptionAudiologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

UNLABELLED: BACKGROUND/STUDY CONTEXT: Arousal and negative affect modulate the effect of emotion on the subjective experience of the passage of time. Given that older adults are less aroused by negative emotional stimuli, and report lower levels of negative affect, compared with younger adults, the present study examined whether the effect of emotion on time perception differed in older and younger adults. METHODS: Participants performed a temporal bisection task for emotional (i.e., angry, sad, happy) and neutral facial expressions presented at varying temporal intervals. RESULTS: Older adults perceived the duration of both positive and threatening events longer than neutral events, whereas younger adults only perceived threatening events longer than neutral events. CONCLUSION: The results, which are partially consistent with the positivity effect of aging postulated by the socioemotional selectivity theory, are the first to show how the effect of emotion on perceived duration affects older adults, and support previous research indicating that only threatening events prolong perceived duration in younger 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0040.000

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 head0.117
GPT teacher head0.445
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations18
Published2013
Admission routes1
Has abstractyes

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