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Record W2332579724 · doi:10.1037/h0095082

Teaching in a new key: Effects of a co-taught seminar on medical students' attitudes toward schizophrenia.

2001· article· en· W2332579724 on OpenAlexaff
Shalom Coodin

Bibliographic record

VenuePsychiatric Rehabilitation Journal · 2001
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Perspective (graphical)PsychologyHealth professionalsMedical educationPsychiatryMedicineHealth care

Abstract

fetched live from OpenAlex

In order to examine the effect of a consumer and professional co-taught seminar on recovery in persons with schizophrenia, fourth year medical students completed attitudinal surveys at the beginning and end of their 7-week rotation in psychiatry. Analysis of results comparing average change in scores in a group exposed to the seminar (n = 24) and a control group not exposed (n = 10), shows measurable change in some survey items indicative of attitudinal change. Such a teaching format may provide a broader perspective on the long term issues for persons with schizophrenia. This can serve to counter the limitations of the brief exposure students receive to hospitalized patients in the most debilitating phase of the illness. The co-teaching model may provide a new and balanced perspective for medical students, facilitating a more holistic understanding of patients and countering a possible overemphasis on diagnosis. Such a format could have application in teaching psychiatric residents, nurses, and other health professionals.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.021
GPT teacher head0.439
Teacher spread0.418 · 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 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

Citations50
Published2001
Admission routes1
Has abstractyes

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