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Record W4381094970 · doi:10.1016/j.ajpe.2023.100550

Is it Time for Competency-Based Education to Move Forward in Pharmacy Education?

2023· article· en· W4381094970 on OpenAlexaff
Zubin Austin, Dorothy A. Andriole, Denise H. Rhoney

Bibliographic record

VenueAmerican Journal of Pharmaceutical Education · 2023
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPharmacyPharmacy educationMedical educationQuality (philosophy)Pharmacy practiceHealth professionsMedicineHigher educationHealth carePolitical scienceNursing

Abstract

fetched live from OpenAlex

Competency-based education is rapidly emerging as a paradigmatic shift in health professions education, as we grapple with the realities of ever-changing and increasing demands of society and health systems. While pharmacy educators are becoming more familiar with this paradigm, colleagues in medical education have been exploring models and methods of competency-based education for many years, and their experiences can be illuminating for us. The persistent question that drives continuous quality improvement in pharmacy education and the development of initiatives within American Association of Colleges of Pharmacy might be stated as "Is there a better (more effective, more efficient) way to prepare pharmacists (future and current) to meet the medication-related needs of the public?"

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.468
Teacher spread0.433 · 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 designNot applicable
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

Citations11
Published2023
Admission routes1
Has abstractyes

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