East meets West: Shadow coaching to support online reflective practice
Bibliographic record
Abstract
OBJECTIVES: A structured, reflection-based electronic portfolio program (ePortfolio), with novel faculty development initiative, involving 'shadow coaches', was shared with the newly formed Ottawa-Shanghai Joint School of Medicine (OSJSM). OSJSM is a partnership between Shanghai Jiao Tong University and the University of Ottawa. As the world's first Sino-Canadian Joint Medical School, OSJSM introduced North American undergraduate medical curriculum to China. 'Shadow coaching' involved trans-Pacific pairing of coaches, supplemented by local faculty development. FRAMEWORK: (a) Pre-implementation: The well-established online ePortfolio platform at the University of Ottawa was mirrored at OSJSM. University of Ottawa ePortfolio coaches were recruited to serve as shadow coaches to their OSJSM counterparts. Shadow coaches provided mentoring and resources while maintaining awareness of cross-cultural issues. Faculty development consisted of face-to-face faculty development in Shanghai, several online synchronous sessions, and familiarization of University of Ottawa coaches with the Chinese medical education system. (b) Description/Components: This intervention, introduced in 2016-2017, involved five University of Ottawa shadow coaches paired with five OSJSM ePortfolio coaches. Student reflection encourages open frank discussion which is a new paradigm for Chinese students and faculty. Shadow coaches were encouraged to challenge new OSJSM coaches to widely explore physician roles and competencies. RESULTS: Initial results indicate that the experience served to effectively develop OSJSM coaches' skills as evidenced by shadow coaches' review of anonymized OSJSM student reflective writing. CONCLUSIONS: Our project describes a novel tool using shadow coaching for faculty development for a cross-cultural partnership. Similar approaches can be utilized for culturally-sensitive long-distance faculty development.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".