Self‐Efficacy and the Prediction of Domain‐Specific Cognitive Abilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We evaluated predictors of performance in 4 specific cognitive ability domains: verbal, numerical, spatial, and mechanical. The predictors were individual differences in self-efficacy beliefs, self-enhancement tendencies, and cross-domain abilities. Our university students' beliefs about their verbal, numerical, and spatial capabilities correlated well with their actual performance on standardized tests (verbal r=.33, numerical r=.27, spatial r=.36). In contrast, the students' self-efficacy for mechanical tasks did relatively poorly in predicting mechanical test performance (r=.10). Most interesting were two other findings: (a) The best predictor of domain performance was level of cross-domain performance by far, even for mechanical tasks, and (b) self-enhancement tendencies added to cross-domain abilities and self-efficacy beliefs in the prediction of performance. The results are discussed in terms of possible mechanisms explaining how one's score on a maximal performance task can be affected by self-efficacy beliefs and self-enhancement tendencies.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it