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Record W2947497445

Best Practices in Bridging Education: Multiple Case Study Evaluation of Postsecondary Bridging Programs for Internationally Educated Health Professionals.

2018· article· en· W2947497445 on OpenAlexaffabout
Elena Neiterman, Ivy Lynn Bourgeault, Julie Peters, Victoria M. Esses, Elaine Dever, Rae Gropper, Christine Nielsen, Jenna Kelland, Peggy Sattler

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBridging (networking)CurriculumMedical educationAllied health professionsProfessional developmentGovernment (linguistics)Public relationsMedicineHealth careBusinessPsychologyPolitical sciencePedagogyComputer science
DOInot available

Abstract

fetched live from OpenAlex

AIMS: Bridging education for internationally trained professionals has grown in popularity, but little is known about promising practices for bridging education in allied health professions. This paper addresses this gap by examining the expected outcomes of effective bridging programs, the key features that contribute to their effectiveness, challenges faced by bridging programs, and the appropriate role of regulatory colleges, government, employers, and professional associations in bridging education. METHODS: We conducted a mixed-methods multiple case study analysis of seven bridging programs in Ontario, Canada, in five allied health professions: medical laboratory technology, medical radiation technology, diagnostic medical sonography, respiratory therapy, and physical therapy. RESULTS: Effective bridging programs are accessible and flexible in content and format. The key challenges include developing curricula tailored to participants' needs, identifying appropriate format for program delivery, obtaining clinical placements for participants, and achieving financial sustainability. Government, professional, and educational stakeholders should play a central role in bridging education planning and delivery. CONCLUSION: The success of a bridging program relies on two key components-program design and infrastructure. Partnerships with government, professional, and educational stakeholders facilitate the development of good bridging programs.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.685
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.156
GPT teacher head0.455
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

Citations9
Published2018
Admission routes2
Has abstractyes

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