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Record W2982595345 · doi:10.4103/jfmpc.jfmpc_551_19

Views of physicians on the establishment of a department of family medicine in South India: A qualitative study

2019· article· en· W2982595345 on OpenAlexaff
SajithaM. F. Rahman, Evelyn Vingilis, Saadia Hameed

Bibliographic record

VenueJournal of Family Medicine and Primary Care · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsWestern University
Fundersnot available
KeywordsMentorshipMedicineQualitative researchFamily medicineThematic analysisNursingHealth careInstitutionAlternative medicineMedical education

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the experiences and perceptions of physicians involved in establishing a department of Family Medicine in South India. METHODS: In this study, descriptive qualitative methodology was used. Nine family physicians and one community medicine physician were interviewed. The data were subjected to thematic analysis. FINDINGS: The establishment of a department of Family Medicine in South India in response to the local health-care demands needed support from the institution, visionary leaders and alumni of the institution. The key challenges perceived were lack of mentorship, lack of identity and misunderstanding of the work of family physicians. CONCLUSION: This study replicates earlier studies on the role of local health-care needs and visionary leaders in striving towards family medicine-based clinical services that further evolved into training and research opportunities in family medicine. The study identified the challenges and supportive forces behind the initiation of a department of Family Medicine and the role of family physicians in strengthening primary health care.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.139
GPT teacher head0.466
Teacher spread0.327 · 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 designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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