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Record W2095424959 · doi:10.1080/10398560601123740

Mentoring Young Researchers: Can the Donald J Cohen Fellowships Model be Applicable and useful to Australasian Psychiatry?

2007· article· en· W2095424959 on OpenAlexaff
Robert Adler, Andrés Martin, Chohye Park, Joseph M. Rey, Susan Tan

Bibliographic record

VenueAustralasian Psychiatry · 2007
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsCommonwealthSession (web analytics)Government (linguistics)Presentation (obstetrics)Child and adolescent psychiatryMedical educationPsychologyLibrary scienceMedicinePolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.354
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2007
Admission routes1
Has abstractyes

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