A critical review of representation in the development of global oncology curricula and the influence of neocolonialism
Bibliographic record
Abstract
BACKGROUND: Global curricular homogenization is purported to have a multitude of benefits. However, homogenization, as typically practiced has been found to promote largely Western ideals. The purpose of this study was to explore the issue of representation in the development of global oncology curricula. METHODS: This systematic review of global oncology curricula involved a comprehensive search strategy of eight databases from inception to December 2018. Where available, both controlled vocabulary terms and text words were used. Two investigators independently reviewed the publications for eligibility. Full global/core oncology curricular documents were included. Data analysis included exploration of representation across a number of axes of power including sex and geographic sector, consistent with a neocolonial approach. RESULTS: 32,835 documents were identified in the search and 17 remained following application of the inclusion/exclusion criteria. Eleven of 17 papers were published from 2010 to 2018 and 13 curricula originated from Europe. The 17 curricula had 300 authors; 207 were male and most were from Europe (n = 190; 64%) or North America (n = 73; 24%). The most common curricular purposes were promoting quality patient care (n = 11), harmonization of training standards (n = 10), and facilitating physician mobility (n = 3). The methods for creation of these curricula were most commonly a committee or task force (n = 10). Over time there was an increase in the proportion of female authors and the number of countries represented in the authorship. CONCLUSION: Existing global oncology curricula are heavily influenced by Western male authors and as a result may not incorporate relevant socio-cultural perspectives impacting care in diverse geographic settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.031 | 0.026 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".