Mentoring Young Researchers: Can the Donald J Cohen Fellowships Model be Applicable and useful to Australasian Psychiatry?
Bibliographic record
Abstract
OBJECTIVES: To describe the experience with the Donald J Cohen Fellowship program of the International Association for Child and Adolescent Psychiatry and Allied Professions (IACAPAP) and examine whether this model may be applied by the RANZCP to attract and support young researchers in Australasia. METHODS: The program at the September 2006 IACAPAP conference included 50 young researchers, 16 mentors and 8 'host fellows', and consisted of exclusive poster sessions, daily small-group mentoring meetings, oral presentation of selected papers, and a summary and feedback session. RESULTS: Informal feedback from mentors, mentees and conference organisers was very positive. CONCLUSIONS: A proposal about funding, participants and activities is presented. This suggests that a mentoring model similar to the Donald J Cohen Fellowship program can be easily conducted in Australasia. Implementing a program of this type would give College Fellows, the Australian Medical Council, the Commonwealth Government and other relevant organizations a clear message that the RANZCP is seriously committed to fostering and supporting research.
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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 | 0.057 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".