High Self-Efficacy and Precrastination: Task Order Choices Based on Deadline Proximity
Bibliographic record
Abstract
The concept of ‘precrastination’ as opposed to procrastination has emerged. Precrastination describes scenarios where individuals initiate tasks sooner, even when at a cost or extra effort, to possibly alleviate cognitive load. Recent literature has explored the merits of delaying or promptly addressing aversive tasks. When confronted with aversive tasks, conventional wisdom suggests addressing them immediately. Recent research has underscored the advantages of prompt task completion, even if it incurs additional costs. Nevertheless, the optimal task order remains elusive. Moreover, the influence of situational factors and individual differences on task sequencing is not fully understood. This study specifically examined the interaction between the proximity of deadlines and self-efficacy to clarify their combined effects on task order preferences. Results indicated that individuals with high self-efficacy tend to start with their preferred task when the deadline is distant but conduct aversive tasks first when the deadline is imminent. This paper suggests that people with high self-efficacy strategically sequence tasks, optimizing efficiency based on situational demands.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".