Metamotivational beliefs about intrinsic and extrinsic motivation.
Bibliographic record
Abstract
= 3,544), participants provided beliefs about the utility of different types of motivation-regulation strategies: strategies that enhance one's interest and enjoyment in a task versus strategies that focus on the value associated with task outcomes (self-relevance strategies and reward strategies). Across all studies, participants recognized that the adaptiveness of these strategies depends on the nature of the task being completed. Consistent with an understanding of normative task-motivation fit, participants generally reported that interest-enhancing strategies were more useful for open-ended tasks and that reward strategies were more useful for closed-ended tasks; however, in some studies, participants reported that reward strategies were equally useful across task types (Studies 2, 3, and 5). More normatively accurate beliefs were associated with more normatively accurate consequential behavioral choices (Study 6) and better task performance (Study 7). We discuss the implications of these results for theories of motivation and self-regulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".