Collaborative autonomy: The dynamic relations between personal goal autonomy and perceived autonomy support in emerging adulthood results in positive affect and goal progress
Bibliographic record
Abstract
Individuals are more successful when they pursue autonomous goals, but how do such goals develop in young adults? The current investigation suggests that the development of autonomous personal goals is a collaborative process. To test this, we examined whether autonomous motivation and autonomy support would interact in a dynamic reciprocal manner over the school year. A 5-wave longitudinal study was conducted with university students (N = 1544), who completed surveys on motivation, support, goal progress and affect. A dynamic reciprocal relation emerged between autonomous motivation and autonomy support. At each subsequent time-point, autonomy support led to increased autonomous motivation, and autonomous motivation led to increased autonomy support. This upward spiral of autonomous goal motivation and autonomy support also resulted in increased positive affect and goal progress over the academic year. These results suggest that the development of autonomous personal goals is a collaborative process fueled by an individual’s personal autonomy and the interpersonal autonomy support they perceive from others, and this upward cycle is also beneficial for well-being and success. Future research is needed to determine how autonomously motivated individuals seek or elicit more autonomy support from others.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".