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Record W4382198479 · doi:10.1177/17456916231178553

For Whom (and When) the Time Bell Tolls: Chronotypes and the Synchrony Effect

2023· article· en· W4382198479 on OpenAlexafffund
Cynthia P. May, Lynn Hasher, Karl Healey

Bibliographic record

VenuePerspectives on Psychological Science · 2023
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute on AgingNational Science Foundation
KeywordsChronotypeEveningPsychologyMorningCognitionArousalDevelopmental psychologyNeuropsychologyCircadian rhythmCognitive psychologySocial psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Circadian rhythms are powerful timekeepers that drive physiological and intellectual functioning throughout the day. These rhythms vary across individuals, with morning chronotypes rising and peaking early in the day and evening chronotypes showing a later rise in arousal, with peaks in the afternoon or evening. Chronotype also varies with age from childhood to adolescence to old age. As a result of these differences, the time of day at which people are best at attending, learning, solving analytical problems, making complex decisions, and even behaving ethically varies. Across studies of attention and memory and a range of allied areas, including academic achievement, judgment and decision-making, and neuropsychological assessment, optimal outcomes are found when performance times align with peaks in circadian arousal, a finding known as the synchrony effect. The benefits of performing in synchrony with one’s chronotype (and the costs of not doing so) are most robust for individuals with strong morning or evening chronotypes and for tasks that require effortful, analytical processing or the suppression of distracting information. Failure to take the synchrony effect into consideration may be a factor in issues ranging from replication difficulties to school timing to assessing intellectual disabilities and apparent cognitive decline in aging.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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 designTheoretical or conceptual
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
Published2023
Admission routes2
Has abstractyes

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