The Central Governor Model of Exercise Regulation Teaches Us Precious Little about the Nature of Mental Fatigue and Self-Control Failure
Bibliographic record
Abstract
Self-control is considered broadly important for many domains of life. One of its unfortunate features, however, is that it tends to wane over time, with little agreement about why this is the case. Recently, there has been a push to address this problem by looking to the literature in exercise physiology, specifically the work on the central governor model of physical fatigue. Trying to explain how and why mental performance wanes over time, the central governor model suggests that exertion is throttled by some central nervous system mechanism that receives information about energetic bodily needs and motivational drives to regulate exertion and, ultimately, to prevent homeostatic breakdown, chiefly energy depletion. While we admire the spirit of integration and the attempt to shed light on an important topic in psychology, our concern is that the central governor model is very controversial in exercise physiology, with increasing calls to abandon it altogether, making it a poor fit for psychology. Our concerns are threefold. First, while we agree that preservation of bodily homeostasis makes for an elegant ultimate account, the fact that such important homeostatic concerns can be regularly overturned with even slight incentives (e.g., a smile) renders the ultimate account impotent and points to other ultimate functions for fatigue. Second, despite the central governor being thought to take as input information about the metabolic needs of the body, there is no credible evidence that mental effort actually consumes inordinate amounts of energy that are not already circulating in the brain. Third, recent modifications of the model make the central governor appear like an all-knowing homunculus and unfalsifiable in principle, thus contributing very little to our understanding of why people tend to disengage from effortful tasks over time. We note that the latest models in exercise physiology have actually borrowed concepts and models from psychology to understand physical performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".