On the Hierarchical Structure of Self-Determined Motivation: A Test of Top-Down, Bottom-Up, Reciprocal, and Horizontal Effects
Bibliographic record
Abstract
This article aimed to test some hypotheses about the hierarchical structure of self-determined motivation in two longitudinal studies. First, the authors verified the stability of global self-determined motivation and school self-determined motivation over time. Second, they tested top-down, bottom-up, reciprocal, and horizontal effects between global self-determined motivation and school self-determined motivation. In Study 1, 122 college students were evaluated on two occasions with a 5-year interval on their global and school self-determined motivation. In Study 2, 294 college students were evaluated on the same variables with a 1-year interval. Results from both studies revealed that (a) global self-determined motivation was not more stable than self-determined school motivation over time and (b) a cross-lag model including reciprocal effects between self-determined global and self-determined school motivation offered the best fit indices comparatively to a model involving only horizontal (or stability) effects. Discussion emphasizes the theoretical implications of the results.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".