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Record W4327786589 · doi:10.1079/searchrxiv.2023.00155

International Credential Equivalency (CINAHL).

2023· article· en· W4327786589 on OpenAlexaffabout
Mark R. Lafave, Yasaman Ammanejad, Breda Eubank, Ulkar Mammadova

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMount Royal University
Fundersnot available
KeywordsCredentialCINAHLImmigrationContext (archaeology)WorkforceHealth carePublic relationsHealthcare systemHealth professionalsPolitical scienceKnowledge managementEngineering ethicsMedical educationMedicineMEDLINEComputer scienceEngineeringGeography

Abstract

fetched live from OpenAlex

Covell et al (9) completed a scoping review with the primary goal of integrating internationally educated health professionals into the Canadian healthcare system. The goal of this review was to synthesize all the literature related to policies that impact immigration into Canada. The goals of our scoping review are similar to those identified by Covell et al with the following distinctions: The most significant goal will be to determine the system(s) that is/are employed to establish international equivalency of a professional with the ultimate goal of immigration and professional practice in a country that is different than their original domestic education.(9) Another significant difference of our scoping review will be to include a wider definition beyond the healthcare workforce since equivalency systems from other non-healthcare related professions may be applicable across multiple disciplines. Finally, the last difference is that the literature will not be limited to Canadian systems, even though there is a focus on the Canadian context.

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)0.012
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.187
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.093
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0560.064
Science and technology studies0.0020.001
Scholarly communication0.0070.005
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1870.022

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 head0.103
GPT teacher head0.512
Teacher spread0.409 · 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 designNot applicable
Domainnot available
GenreOther

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

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