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Record W7098033254

Canadian University Faculties of Pharmacy: Undergraduate Curriculum Survey of Geriatric Content

2008· article· en· W7098033254 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyCurriculumGeriatricsClinical pharmacyPharmacy practicePharmacy educationCurriculum development
DOInot available

Abstract

fetched live from OpenAlex

The present geriatric content of undergraduate education in Canadian pharmacy schools was examined. A 35-item survey covering a range of educational topics was sent to relevant faculty members at each of the Canadian schools of pharmacy. All nine Canadian faculties of pharmacy responded. Only three schools had a separate geriatric course, the rest had integrated geriatric content. Both clinical and didactic courses were taught primarily by pharmacy faculty, and rarely by medicine faculty. Established guidelines surrounding inappropriate prescribing practices in the elderly were specifically taught in most schools. Innovative strategies included role playing, geriatric therapeutics “hot-lines ” manned by pharmacy students, geriatric education modules, and geriatric pharmacology textbooks written by faculty members. The variability in the geriatric curriculum could be addressed with a mandatory geriatric issues pharmacy course. Partnerships with academic divisions of geriatric medicine and clinical pharmacology could further enrich the educational experience for pharmacy and medical students.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.236
GPT teacher head0.361
Teacher spread0.125 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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