Testing a continuum structure of self-determined motivation: A meta-analysis.
Bibliographic record
Abstract
Self-determination theory proposes a multidimensional representation of motivation comprised of several factors said to fall along a continuum of relative autonomy. The current meta-analysis examined the relationships between these motivation factors in order to demonstrate how reliably they conformed to a predictable continuum-like pattern. Based on data from 486 samples representing over 205,000 participants who completed 1 of 13 validated motivation scales, the results largely supported a continuum-like structure of motivation and indicate that self-determination is central in explaining human motivation. Further examination of heterogeneity indicated that while regulations were predictably ordered across domains and scales, the exact distance between subscales varied across samples in a way that was not explainable by a set of moderators. Results did not support the inclusion of integrated regulation or the 3 subscales of intrinsic motivation (i.e., intrinsic motivation to know, to experience stimulation, and to achieve) due to excessively high interfactor correlations and overlapping confidence intervals. Recommendations for scale refinements and the scoring of motivation are provided. (PsycINFO Database Record
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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 | 0.041 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.017 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".