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Record W1975994810 · doi:10.1007/s00268-007-9243-8

Ethics of Surgical Training in Developing Countries

2007· article· en· W1975994810 on OpenAlexaff
Kevin M. Ramsey, Charles Weijer

Bibliographic record

VenueWorld Journal of Surgery · 2007
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsWestern University
Fundersnot available
KeywordsHarmCompetence (human resources)MedicineDeveloping countryEthical issuesVascular surgeryMedical educationNursingEngineering ethicsCardiac surgeryPsychologySurgery

Abstract

fetched live from OpenAlex

The practice of surgical trainees operating in developing countries is gaining interest in the medical community. Although there has been little analysis about the ethical impact of these electives, there has been some concerns raised over the possible exploitation of trainees and their patients. An ethical review of this practice shows that care needs to be taken to prevent harm. Inexperienced surgeons learning surgical skills in developing countries engender greater risk of violating basic ethical principles. Advanced surgical trainees who have already achieved surgical competence are best qualified to satisfy these ethical issues. All training programs need to develop a structured ethical review for international electives to protect their trainees and their patients from harm.

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)0.034
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.023
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.101
GPT teacher head0.371
Teacher spread0.271 · 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 designTheoretical or conceptual
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

Citations42
Published2007
Admission routes1
Has abstractyes

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