Examining Procrastination Across Multiple Goal Stages: A Longitudinal Study of Temporal Motivation Theory
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".