MétaCan
Menu
Back to cohort
Record W4387256983 · doi:10.46542/pe.2023.231.594602

The case of clinical training for International Pharmacists in Canada: A comparative educational and policy analysis

2023· article· en· W4387256983 on OpenAlexaffabout
Amad Al-Azzawi

Bibliographic record

VenuePharmacy Education · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPharmacyClinical pharmacyTraining (meteorology)MedicineMedical educationFamily medicineNursingPolitical scienceGeography

Abstract

fetched live from OpenAlex

Background: The passing rate for International Pharmacists is much lower than that of domestic pharmacy graduates in the licensing examination in Canada. This study aimed to examine differences in policies and educational infrastructure systems integrated that help shape advanced clinical training for International Pharmacists in the different provinces. Method: This study used a comparative policy analysis of regulations governing International Pharmacists in three provinces, including Ontario, Alberta, and British Columbia. Results: When examining current integration systems in these provinces, differences in clinical training period requirements become apparent. For example, Alberta and British Columbia have already started efforts towards better integration frameworks in clinical training for international pharmacists. However, there is a need for more unified and inclusive measures towards the integration of international experiences within the Canadian pharmacy practice system across all three provinces. Conclusion: The Canadian model lacks a clinical training period before the qualifying examination, unlike other models around the world.

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)0.001
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 score0.172
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.356
GPT teacher head0.656
Teacher spread0.299 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePharmacy EducationSame topicGlobal Health Workforce IssuesFrench-language works237,207