Developing a Training Program to Improve Supervisor-Resident Relationships, Step 1: Defining the Types of Issues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: By some estimates, the teacher-learner relationship explains roughly half of the variance attributed to the effectiveness of teaching. Despite this, relationships largely have been ignored in the educational literature. PURPOSE: This qualitative pilot study sought to identify factors in the supervisor-resident relationship that hinder learning among University of Toronto psychiatry residents. METHOD: Thirteen postgraduate-year residents in Years 2-5 and their supervisors were interviewed regarding interactions that either assisted or adversely affected learning. RESULTS: Qualitative analysis of the interview data led to the identification of 5 types of issues affecting the supervisory relationship: goals and individual differences, communication and feedback, power and rivalry, support and collegiality, and role modeling and expertise. Face validity was supported when typed anonymous written feedback obtained from annual supervisor evaluations also could be organized into the 5 categories. CONCLUSIONS: Recognition of the types of interpersonal interactions that assist or hinder learning may contribute to enhanced teaching effectiveness.
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.
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 | 0.022 | 0.032 |
| 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 | 0.000 | 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 it