Autonomous motivation and support flourishes for individuals higher in collaborative personality factors: Agreeableness, assisted autonomy striving, and secure attachment
Bibliographic record
Abstract
INTRODUCTION: Individuals who strive autonomously for their goals, and who perceive autonomy supportive environments are more successful during goal pursuit. What dispositional factors predict autonomy flourishing during goal pursuit? METHODS: = 1,544) completed surveys on motivation, support, and personality. Structural equation models were created using Mplus software to test whether collaborative personality factors were related to growth in autonomous motivation and autonomy support. RESULTS: All three distinct collaborative personality factors, trait Agreeableness, assisted autonomy striving, and secure parental attachment, were related to increases in autonomous motivation over the academic year. Conscientiousness, assisted autonomy, and secure attachment were related to increases in perceived autonomy support. A higher order latent collaborative traits factor, composed of Agreeableness, assisted autonomy, and secure attachment was found to be related to increased autonomous motivation and support over the academic year and resulted in increased goal progress. CONCLUSION: These results suggest that individuals higher in collaborative personality factors experience growth in personal autonomy during goal pursuit. Future research is needed to determine how to promote collaboration in goal pursuit to further help individuals successfully strive for their goals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".