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Record W2570830660 · doi:10.36834/cmej.36757

Support infrastructure available to Canadian residents completing post-graduate global health electives: current state and future directions

2016· article· en· W2570830660 on OpenAlexaffvenueabout
Lojan Sivakumaran, Tasha Ayinde, Fadi Hamadini, Sarkis Meterissian, Tarek Razek, Robert Puckrin, Johanna Muñoz, Shawna O’Hearn, Dan Deckelbaum

Bibliographic record

VenueCanadian Medical Education Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsDalhousie UniversityMcGill University Health CentreMcGill University
Fundersnot available
KeywordsDebriefingMedical educationGlobal healthPreparednessPolitical sciencePublic relationsMedicineBusinessPublic healthNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Global health electives offer medical trainees the opportunity to broaden their clinical horizons. Canadian universities have been encouraged by regulatory bodies to offer institutional support to medical students going abroad; however, the extent to which such support is available to residents has not been extensively studied. METHODS: We conducted a survey study of Canadian universities examining the institutional support available to post-graduate medical trainees before, during, and after global health electives. RESULTS: Responses were received from 8 of 17 (47%) Canadian institutions. Results show that trainees are being sent to diverse locations around the world with more support than recommended by post-graduate regulatory bodies. However, we found that the content of the support infrastructure varies amongst universities and that certain components-pre-departure training, best practices, risk management, and post-return debriefing-could be more thoroughly addressed. CONCLUSION: Canadian universities are encouraged to continue to send their trainees on global health electives. To address the gaps in infrastructure reported in this study, the authors suggest the development of comprehensive standardized guidelines by post-graduate regulatory/advocacy bodies to better ensure patient and participant safety. We also encourage the centralization of infrastructure management to the universities' global health departments to aid in resource management.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.418
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.014
GPT teacher head0.335
Teacher spread0.321 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2016
Admission routes3
Has abstractyes

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