The Relations Among Affect-Related Personality Traits, Mood, Temptation and Academic Procrastination in Everyday Life
Bibliographic record
Abstract
The current research study made use of daily diaries and personality assessment to examine academic procrastination behaviour in the everyday lives of university students. Undergraduate students (n = 84) completed self-report measures on trait affect intensity, distress tolerance and emotion regulation difficulties before engaging in ten days of daily diaries. Multilevel regression analyses were used to examine whether within-person variations in the intensity of experienced negative moods and temptations predicted levels of self-reported procrastination behaviour, and whether these relations were moderated by individual differences in affect-related personality traits. As hypothesized, at the day-level of analysis, both the extent of negative affect and the strength of experienced temptations positively predicted levels of academic procrastination behaviour. Contrary to what was hypothesized, none of the affect-related personality traits directly or indirectly predicted procrastination behaviour, except for trait levels of emotion regulation difficulties which positively predicted average levels of daily procrastination behaviour.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".