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Record W1973789143 · doi:10.3109/10398560903414136

Evaluation of the Claassen Institute of Psychiatry for Medical Students

2010· article· en· W1973789143 on OpenAlexaff
Zaza Lyons, Brian Power, Natalia Bilyk, Jodi Lofchy, Johann Claassen

Bibliographic record

VenueAustralasian Psychiatry · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBaseline (sea)Medical educationPsychologyPsychiatrySpecial Interest GroupMedical schoolChild and adolescent psychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Psychiatric educators need to develop innovative strategies to attract more medical students to psychiatry. In 2008, the University of Western Australia held the inaugural Claassen Institute of Psychiatry for Medical Students. This novel program aimed to increase students' level of interest in psychiatry as a career opportunity. METHOD: Students completed baseline and follow-up questionnaires. Questions were rated on a scale of 1 to 10. RESULTS: Thirty students participated. The average age was 25.5 years and 11 were male. The mean interest and knowledge in psychiatry from baseline to follow-up increased from 7.8 to 8.9 and 5.8 to 7.3, respectively. Mean interest and knowledge in neurosciences increased from 6.9 to 7.7 and 4.3 to 6.2, respectively. Paired t sample tests were significant (p<0.001). Students 'definitely considering' a career in psychiatry increased by 20% overall from baseline to follow-up. Enjoyment and organization of the week were rated highly. CONCLUSIONS: The Institute is an innovative teaching strategy targeted towards medical students. The program increased the level of interest shown by students in psychiatry as a career. The Institute may positively contribute to recruitment of students to psychiatry training programs and it is planned to run it annually.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.378
Teacher spread0.350 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2010
Admission routes1
Has abstractyes

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