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Record W2003216901 · doi:10.1080/10398560902964602

The University of Western Australia Institute of Psychiatry for Medical Students: An Australian First

2009· article· en· W2003216901 on OpenAlexaboutno aff
Zaza Lyons, Brian Power, Natalia Bilyk, Johann Claassen

Bibliographic record

VenueAustralasian Psychiatry · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationPerspective (graphical)PsychiatryPsychologyMedicineFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Recruitment of medical graduates into psychiatry has become a growing issue over the last few decades. This paper describes the implementation of an innovative program, based on a Canadian concept, that aimed to promote psychiatry as a career choice to medical students, to immerse them in the 'world of psychiatry', and introduce them to potential mentors. The University of Western Australia Institute of Psychiatry for Medical Students was a week-long program that provided medical students with an opportunity to participate in a diverse agenda of interactive seminars on a range of psychiatric subspecialties and the neurosciences. Students were also able to attend elective sessions and meet registrars and psychiatrists on an informal basis. Lunches and social events were also provided. CONCLUSION: Twenty-one students attended the inaugural Institute. Twenty-seven speakers contributed to the morning seminars and there were 17 clinical elective site visits. Feedback from students was positive and the week was rated highly, both in terms of its organization and from an academic perspective. It is planned to run the Institute annually and, in time, it is hoped that it will increase the numbers of students who choose psychiatry as a career option.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.003

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 head0.025
GPT teacher head0.339
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2009
Admission routes1
Has abstractyes

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