A Test of Learned Industriousness in the Physical Activity Domain
Bibliographic record
Abstract
Background: The Theory of Learned Industriousness states that durable individual differences in industriousness are due in part to differences in the extent to which individuals were rewarded for high effort at an earlier time. Individuals rewarded for high effort during training are thought to generalize greater persistence to subsequent tasks than those rewarded for low effort. This study tested whether rewarded physical and/or mental effort at different intensities generalized to greater persistence at a subsequent mental task. Methods: 80 inactive 18-25 year-olds were randomized into four groups: Low Mental Effort, High Mental Effort, Low Physical Effort, and High Physical Effort. Each completed group-specific effort training and a mental persistence task at baseline and posttest. Results: Factorial analysis of covariance revealed a significant domain x effort interaction on persistence (F[1,75]=4.93, p=.029). High Mental Effort and Low Mental Effort groups demonstrated similar gains in persistence (d=-0.08, p>.05) and points earned (d=0.11, p>.05) following effort training. High Physical Effort and Low Physical Effort diverged on persistence (d=-0.49, p=.004) but not points earned (d =-0.12, p>.05). Conclusions: Findings suggest either that training and test stimuli were too dissimilar to cue effects of associative learning in physical effort groups, or that effects were present but overpowered by the affective and neurocognitive consequences of an acute bout of intense aerobic physical activity. Findings do not support the Theory of Learned Industriousness nor generalization of effort across physical and mental domains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".