A pre-registered naturalistic observation of within domain mental fatigue and domain-general depletion of self-control
Bibliographic record
Abstract
Self-control is often believed to operate as if it were a finite, domain-general resource. However, recent attempts to demonstrate this under transparent conditions have failed to yield positive results. In the current study, we monitor two groups of students (N1 = 8,867, N2 = 8,754) over separate 17-week intervals with 24-hour coverage, as they engage in voluntary learning and self-testing using an online program. We use daily behavior to assess whether time-of-day effects support domain-general theories of self-control. Additionally, we assess whether mental fatigue emerges within task during prolonged persistent effort. Results reveal within-task fatigue emerges within an hour on-task. However, there is a negligible effect on ability throughout the day. Additionally, time-of-day has no detrimental effect on motivation; rather there is a strong tendency to increase learning time at night. Results are consistent with theories indicating people lose motivation within a specific task, but at odds with theories that argue for a domain-general self-control resource.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".