Procrastination's Impact in the Workplace and the Workplace's Impact on Procrastination
Bibliographic record
Abstract
Procrastination is a self‐regulatory failure, whose costs are debated. Here, we establish its impact in the workplace. Using an Internet sample, we assessed 22,053 individuals in terms of their sex, employment status, employment duration, income, occupational attainment and level of procrastination. High levels of procrastination is associated with lower salaries, shorter durations of employment, and a greater likelihood of being unemployed or under employed rather than working full‐time. Also, procrastination partially mediates sex's relationship with these work variables. Women tend to procrastinate less than men, evidently giving women an employment advantage. If women procrastinated the same as men, there should be 1.5 million fewer women in full‐time employment in the US. alone. Determining the causes of procrastination in the workplace, we also examined it at an occupational level. The results strongly support the gravitational hypothesis: jobs that require higher levels of motivational skills are less likely to retain procrastinators. However, there was some support that jobs can foster procrastination. Procrastinators tend to have jobs that are lower in intrinsically rewarding qualities.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".