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Record W2795788523 · doi:10.3389/fpsyg.2018.00327

Examining Procrastination Across Multiple Goal Stages: A Longitudinal Study of Temporal Motivation Theory

2018· article· en· W2795788523 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

VenueFrontiers in Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProcrastinationPsychologyTemptationAutomaticityLongitudinal studySocial psychologyAction (physics)Variance (accounting)Cognitive psychologyStatisticsCognition

Abstract

fetched live from OpenAlex

Procrastination is among the most common of motivational failures, putting off despite expecting to be worse off. We examine this dynamic phenomenon in a detailed and realistic longitudinal design (Study 1) as well as in a large correlational data set (N = 7400; Study 2). The results are largely consistent with temporal motivation theory. People's pacing style reflects a hyperbolic curve, with the steepness of the curve predicted by self-reported procrastination. Procrastination is related to intention-action gaps, but not intentions. Procrastinators are susceptible to proximity of temptation and to the temporal separation between their intention and the planned act; the more distal, the greater the gap. Critical self-regulatory skills in explaining procrastination are attention control, energy regulation and automaticity, accounting for 74% of the variance. Future research using this design is recommended, as it provides an almost ideal blend of realism and detailed longitudinal assessment.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.062
GPT teacher head0.372
Teacher spread0.310 · 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