MétaCan
Menu
← Back to cohort
Record W3128343955

Geneeskundeopleidingen op de voormalige Nederlandse Antillen Bonaire, Sint-Eustatius en Saba

2015· article· nl· W3128343955 on OpenAlexaboutno aff
Robbert Duvivier, Marta van Zanten

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2015
Typearticle
Languagenl
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationMedicineMedical education
DOInot available

Abstract

fetched live from OpenAlex

On 10 October 2010, the former Netherlands Antilles was dissolved politically; Curacao and St Maarten became autonomous countries, while Bonaire, St Eustatius and Saba (the 'BES islands') joined the Netherlands with the status 'special municipalities'. At that time there was one medical school on each of the BES islands, providing medical education to students predominantly from the United States and Canada. A process was instigated for recognition and accreditation within the Netherlands system of the education provided by these schools. This article provides an overview of this process, and investigates its consequences, including admission and registration requirements, student mobility and financial aspects. The current location and status of the different educational programmes will be explained.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.134
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0400.006

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 head0.063
GPT teacher head0.384
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueData Archiving and Networked Services (DANS)→Same topicGlobal Health Workforce Issues→French-language works237,207→