MétaCan
Menu
Back to cohort
Record W2034995602 · doi:10.1080/0142159031000137418

An interprofessional problem-based learning course on rehabilitation issues in HIV

2003· article· en· W2034995602 on OpenAlexaff
Patricia Solomon, Penny Salvatori, Dale Guenter

Bibliographic record

VenueMedical Teacher · 2003
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInterprofessional educationRehabilitationMedical educationPerceptionPerspective (graphical)PsychologyCourse (navigation)Problem-based learningQualitative researchHuman immunodeficiency virus (HIV)MedicineNursingHealth carePhysical therapyFamily medicineComputer scienceSociology

Abstract

fetched live from OpenAlex

This study examined students' perceptions of their learning through participation in an interprofessional problem-based course on rehabilitation and HIV. Students representing five health professions participated in an eight-week tutorial course. Qualitative analysis of journals that the students completed throughout the course, and of interviews of the students at completion of the course, revealed that they valued their learning experience. Students gained an appreciation of the roles of others and developed a sense of confidence through justifying their professional role. Through the interprofessional discussions, students were able to increase the breadth and depth of their learning and also gained a rehabilitation perspective. Learning related to HIV and rehabilitation is ideally suited to an interprofessional, problem-based environment.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.464
Teacher spread0.444 · 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

Citations36
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueMedical TeacherSame topicInterprofessional Education and CollaborationFrench-language works237,207