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Expanding Global Surgery Education in Brazil: Perspectives after the 35th Brazilian Surgical Congress

2024· article· en· W4391534609 on OpenAlexaff
Luiza Telles, Ayla Gerk, Letícia Nunes Campos, Sofia Wagemaker Viana, Ana Woo Sook Kim, Natália Zaneti Sampaio, Roseanne Ferreira, Joaquim Murray Bustorff‐Silva, David P. Mooney, Cristina Pires Camargo

Bibliographic record

VenueRevista do Colégio Brasileiro de Cirurgiões · 2024
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPerspective (graphical)Political scienceMedicineMedical educationEconomic growthEconomics

Abstract

fetched live from OpenAlex

The 35th Brazilian Congress of Surgery marked a turning point for surgical education in the country. For the first time, the Brazilian College of Surgeons included Global Surgery on the main congressional agenda, providing a unique opportunity to rethink how surgical skills are taught from a public health perspective. This discussion prompts us to consider why and how Global Surgery education should be expanded in Brazil. Although Brazilian researchers and institutions have contributed to the fields expansion since 2015, Global Surgery education initiatives are still incipient in our country. Relying on successful strategies can be a starting point to promote the area among national surgical practitioners. In this editorial, we discuss potential strategies to expand Global Surgery education opportunities and propose a series of recommendations at the national level.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.349
Teacher spread0.337 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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