On the Assessment of Situational Intrinsic and Extrinsic Motivation: The Situational Motivation Scale (SIMS)1
Bibliographic record
Abstract
The purpose of the present research was to develop and validate a situational (or state) measure of motivation, the Situational Motivation Scale (SIMS). The SIMS is designed to assess the constructs of intrinsic motivation, identified regulation, external regulation, and amotivation (E. L. Deci & R. M. Ryan, 1985, 1991) in field and laboratory settings. Five studies were conducted to develop and vali-date the SIMS. Overall, results show that the SIMS is composed of 4 internally consistent factors. The construct validity of the scale is also supported by correla-tions with other constructs as postulated by current theories. Moreover, the SIMS is responsive to experimental induction as evidenced by data gathered through a laboratory study. In sum, the SIMS represents a brief and versatile self-report mea-sure of situational intrinsic motivation, identified regulation, external regulation, and amotivation. 1This work was supported by grants from le Fonds pour la formation des Chercheurs et l’Aide à la Recherche (FCAR-Québec) and the Social Sciences Humanities Research Council of Canada (SSHRC) to Frédéric Guay and Robert J.Vallerand; Céline Blanchard was supported by a postdoctoral
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".