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Record W3044675775 · doi:10.26633/rpsp.2020.83

Formación de recursos humanos para la salud universal: acciones estratégicas desde las instituciones académicas

2020· article· es· W3044675775 on OpenAlex

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

VenueRevista Panamericana de Salud Pública · 2020
Typearticle
Languagees
FieldMedicine
TopicEthics and bioethics in healthcare
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceMedicinePhilosophy

Abstract

fetched live from OpenAlex

The challenge of moving towards the right to health for all -through the strategies for universal access to health and universal health coverage (universal health)- requires multiple conditions and actions. One of them is to have sufficient health workers, well distributed and with the skills and motivation needed for the transformation of health services and to provide comprehensive and quality responses to people and their communities. This article presents the results of a dialogue between academics from universities in the Americas, and reflects on four essential dimensions: planning, interprofessional training, social responsibility of academic centers, and the use of models of teaching-service-research. These dimensions are fundamental for a comprehensive training of health professionals that contributes to universal health coverage.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
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 head0.108
GPT teacher head0.394
Teacher spread0.286 · 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