Irrational Delay Revisited: Examining Five Procrastination Scales in a Global Sample
Bibliographic record
Abstract
Scales attempting to measure procrastination focus on different facets of the phenomenon, yet they share a common understanding of procrastination as an unnecessary, unwanted, and disadvantageous delay. The present paper examines in a global sample (N = 4,169) five different procrastination scales – Decisional Procrastination Scale (DPS), Irrational Procrastination Scale (IPS), Pure Procrastination Scale (PPS), Adult Inventory of Procrastination Scale (AIP), and General Procrastination Scale (GPS), focusing on factor structures and item functioning using Confirmatory Factor Analysis and Item Response Theory. The results indicated that The Pure Procrastination Scale (PPS; 12 items selected from DPS, AIP, and GPS) measures different facets of procrastination even better than the three scales it is based on. An even shorter version of the PPS (5 items focusing on irrational delay), corresponds well to the 9-item Irrational Procrastination Scale (IPS). Both scales demonstrate good psychometric properties and appear to be superior measures of core procrastination attributes than alternative procrastination scales.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".