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Record W4389328220 · doi:10.4102/phcfm.v15i1.4248

Advancing primary care: Establishing family medicine specialty in Tanzania

2023· article· en· W4389328220 on OpenAlexaff
Eric Aghan, Henry Ziegler, Donatus Mutasingwa, Enica Richard Massawe, Peter Wangwe, Dennis Lyakurwa, Muzdalifat Abeid, Riaz Ratansi, Nadeem Kassam, Esther M. Johnston

Bibliographic record

VenueAfrican Journal of Primary Health Care & Family Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCollege of Family Physicians of CanadaUniversity of Toronto
Fundersnot available
KeywordsTanzaniaMedicineSpecialtyGovernment (linguistics)Primary careFamily medicineAlternative medicineHealth careNursingPrimary health carePublic healthPrivate sectorMedical educationPopulationEconomic growthEnvironmental healthSocioeconomics

Abstract

fetched live from OpenAlex

Family medicine has existed as a training pathway through a private university in Tanzania since 2004. As global calls have increased to embrace primary health care as a pathway to ensuring universal health coverage, so has Tanzania recently turned to explore family medicine as a specialty to improve access to comprehensive, high-quality healthcare for her entire population. This article outlines ongoing efforts to define competencies and skills of a family medicine physician in Tanzania, engage government support and open the first public university training programme for family medicine postgraduate education.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
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 head0.053
GPT teacher head0.398
Teacher spread0.344 · 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
GenreCommentary

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

Citations3
Published2023
Admission routes1
Has abstractyes

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