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Record W2979590071

Framework for ethical international academic partnerships in family medicine: The Besrour Papers: a series on the state of family medicine in Canada and Brazil.

2019· article· en· W2979590071 on OpenAlexaffabout
Béatrice Godard, Janie Giard, David Ponka, Katherine Rouleau

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCollege of Family Physicians of CanadaUniversité LavalThe Quebec Population Health Research Network
Fundersnot available
KeywordsGeneral partnershipAccountabilityTransparency (behavior)BioethicsPublic relationsExcellenceReciprocity (cultural anthropology)Equity (law)Engineering ethicsPolitical scienceHumilityEconomic JusticeMedicineSociologyLawSocial science
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop an ethical framework for collaboration in international academic partnerships in family medicine. COMPOSITION OF THE COMMITTEE: A subgroup of the Besrour Centre of the College of Family Physicians of Canada including family medicine and bioethics experts began to collaborate in 2014 to undertake the development of an ethical framework and tools for the establishment of ethically sound international academic partnerships. METHODS: Following 2 consultative workshops and a wider consultation process with the Besrour Centre global community, the authors developed an ethical framework and tools for approval by the Besrour Centre leadership in November 2017. REPORT: Partnerships are essential to family practice and to the field of international development. The flawed nature of many North-South research partnerships underlines the importance of and need for delineating core principles for ethically sound partnerships, of which 10 have been identified in this process: accountability, cost and efficiencies, excellence, equity, humility, justice, leadership, reciprocity, respect for self-determination, and transparency. Based on these principles, a decision-making framework was created to translate these values into actions and to promote a cohesive and transparent structure for discussions. Fostering fairness, transparency, and consistency in decision making reduces the potential for inequity in a partnership, leading to lasting relationships that endure beyond the scope of a partnership agreement.

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)0.079
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0220.029
Scholarly communication0.0170.006
Open science0.0050.015
Research integrity0.0110.012
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.150
GPT teacher head0.425
Teacher spread0.275 · 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 designTheoretical or conceptual
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
Published2019
Admission routes2
Has abstractyes

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