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Record W4281740544 · doi:10.1308/rcsbull.2022.83

Cultural challenges facing UK surgeons providing education in low and middle income countries

2022· article· en· W4281740544 on OpenAlex
SP Hodgson, Mohamed Abdelrahman, B Jemec, WL Lam, Faith C. Muchemwa, Tanveer Ahmed, SC Tucker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBulletin of The Royal College of Surgeons of England · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsTrillium Health Centre
Fundersnot available
KeywordsLow and middle income countriesWork (physics)Relevance (law)MedicineDeveloping countryPolitical scienceEconomic growthMedical educationPublic relationsEconomicsLawEngineering

Abstract

fetched live from OpenAlex

Surgeons from high income countries such as the UK are well placed to support our surgical colleagues in low and middle income countries by performing educational visits. This paper describes the experience of the British Society for Surgery of the Hand and the British Foundation for International Reconstructive Surgery and Training, which have been supporting educational work delivered by their members since 2010. There have been many lessons learnt, including solving challenges caused by our cultural differences. We outline the challenges and cultural intelligence theory that has helped resolution. These lessons may be of relevance to any surgeons from high income countries undertaking educational work in low and middle income countries.

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.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.000
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 head0.022
GPT teacher head0.269
Teacher spread0.247 · 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