Bibliographic record
Abstract
Family medicine (FM) is an independent and distinct medical specialty in the developed countries such as USA, UK, Australia, and Canada since 1960s. FM teaching is imparted at undergraduate and postgraduate levels in countries such as Nepal, Pakistan, and Sri Lanka. Family practice is the practicing vocation of the majority doctors in India. The practitioners of FM include general practitioners, family physicians, FM specialists, and medical officers in the public sector. Medical students are largely unaware about FM career as this concept is not introduced at MBBS level. Faculty and senior doctors from other disciplines are also not able to answer the queries related to FM as they themselves also have gone through the same education system for last three decades, largely unexposed to the concept of academic family medicine. This article is a compilation of frequently asked questions, and their appropriate responses, presented here to dispel myths and misinformation about FM specialty. The answers are deliberated upon by Dr. Raman Kumar the founder president of the Academy of Family Physicians of India and the chief editor of the Journal of Family Medicine and Primary Care. This article was originally published as an interview in Docplexus, a popular online network and website for medical doctors in November 2015.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".