Six Questions for the Resource Model of Control (and Some Answers)
Bibliographic record
Abstract
The resource model of self-control casts self-control as a capacity that relies on some limited resource that exhausts with use. The model captured our imagination and brought much-needed attention on an important yet neglected psychological construct. Despite its success, basic issues with the model remain. Here, we ask six questions: (i) Does self-control really wane over time? (ii) Is ego depletion a form of mental fatigue? (iii) What is the resource that is depleted by ego depletion? (iv) How can changes in motivation, perception, and expectations replenish an exhausted resource? (v) Has the revised resource model unwittingly become a model about motivation? (vi) Do self-control exercises increase self-control? By providing some answers to these questions - including conducting a meta-analysis of the self-control training literature - we highlight how the resource model needs to be revised if not supplanted altogether.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.032 |
| Scholarly communication | 0.006 | 0.031 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.016 | 0.022 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".