Co-Creating a Transformative Learning Environment Through the Student-Supervisor Relationship: Results of a Social Work Field Placement Duo-Ethnography
Bibliographic record
Abstract
In an in-house third-year social work research placement, a duo-ethnography showed that the student–supervisor relationship had far more impact on transformative learning than the assigned placement tasks. A model for co-creating an environment of transformative learning is described, putting student learning and growth at the center. Attributes that contributed to a transformative learning environment included being Trustworthy, Respectful, Engaging, Caring, and Humble. A range of actions within each of these attributes is described. The findings showed that in this context, a crisis-type of disorienting dilemma did not occur. Rather, transformation evolved as part of a learning outcome that included the development of a professional identity as a social worker. Findings suggested the need for further exploration of the role that humility plays in reducing the power imbalance in the student–supervisor relationship. The importance of addressing self-care and avoiding models that risk perpetuating patriarchy in the student-supervisor relationship were highlighted.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".