Autonomy Versus Independence: Implications for Resident and Faculty Engagement, Performance, and Well-Being
Bibliographic record
Abstract
Description Research shows that when educational leaders support their learners' autonomy, it positively impacts both parties. This is particularly important in graduate medical education (GME), given that there is a strong emphasis on resident performance, evaluation, and development. Unfortunately, GME faculty often misunderstand autonomy as the resident's desire for independence or "freedom," when in fact it refers to the core psychological need to feel volitional and agentic. The distinction is important because volition is not synonymous with independence, and providing freedom can be at odds with strategies that provide true autonomy support. This, in turn, can contribute to the stress, maladjustment, and resident burnout that are already prevalent in medicine. To help remedy this issue, this paper provides an evidence-based guide for medical educators to distinguish autonomy from independence, with specific examples to help translate theory into practice to better support the well-being of the medical community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".