Distilling the essence of general practice: a learning journey in progress
Bibliographic record
Abstract
Over the past 5 years, general practice in the UK has undergone major change. Starting with the introduction of the new GMS contract in 2004, it has continued apace with the establishment of Postgraduate Medical Education Training Board, a GP training curriculum, and nMRCGP. The NHS is developing very differently in the four countries of the UK. Regulation of the profession is under review, and a system of relicensing, recertification, and revalidation is being introduced. The Essence project, initiated by RCGP Scotland in conjunction with International Futures Forum 4 years ago is a constructive response to these changes. It has included learning journeys, a discussion day for GPs, and commissioned short pieces of 100 words from GPs and patients. From an analysis of these, some characteristics of the essence of general practice have been defined. These include key roles and core personal qualities for GPs. It is argued that general practice has important and unique advantages - trust, coordination, continuity, flexibility, universal coverage, and leadership - which mean that it should continue to be central to the development of primary care throughout the UK.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.025 | 0.028 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".