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Record W1652855700 · doi:10.36834/cmej.36595

Training medical students in human rights: a fifteen-year experience in Geneva

2012· article· en· W1652855700 on OpenAlexvenueno aff
Philippe Chastonay, Véronique Zesiger, Jackeline F. Ferreira, Emmanuel Kabengele Mpinga

Bibliographic record

VenueCanadian Medical Education Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsModalitiesMedical educationTypologyPolitical scienceMedicinePublic relationsSociologyLawSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Training health professionals in the field of human rights has long been advocated by the United Nations. Over the past decade some medical schools have introduced health and human rights courses, yet by far not all. This paper describes the objectives and the content of the Health and Human Rights program developed at the Faculty of Medicine, University of Geneva. METHODS: The health and human rights program was developed through the identification of the course objectives, contents, and educational modalities using consensus techniques, and through a step by step implementation procedure integrating multiple evaluation processes. RESULTS: Defined objectives included the familiarization with the concepts, instruments and mechanisms of human rights, the links between health and human rights, and the role of health professionals in promoting human rights. The content ultimately adopted focused on the typology of human rights, their mechanisms of protection, their instruments, as well as social inequalities and vulnerable groups of the population. The implementation proceeded through a step by step approach. Evaluation showed high satisfaction of students, good achievement of learning objectives, and some academic and community impact. CONCLUSIONS: High interest of students for a human rights course is encouraging. Furthermore, the community projects initiated and implemented by students may contribute to the social responsibility of the academic institution.

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)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.000

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 head0.063
GPT teacher head0.430
Teacher spread0.366 · 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 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

Citations7
Published2012
Admission routes1
Has abstractyes

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