A Descriptive Analysis of the Previous Care Experiences of Patients Being Rostered in British Columbia’s New Nurse-Practitioner Primary Care Clinics
Bibliographic record
Abstract
Aim: This article analyzes the previous care experiences and socio-demographic characteristics of patients being rostered in British Columbia’s new Nurse-Practitioner Primary Care Clinics (NP-PCCs) Background: Nurse Practitioner (NP)-led clinics leverage the NPs’ extended scope of practice to increase accessibility to Primary Care. In 2020, British Columbia announced the opening of four Nurse-Practitioner Primary Care Clinics. Methods: This study provides a descriptive analysis of the demographics and previous care experiences of 424 patients newly rostered to one of BC’s new clinics. Findings: The patients rostered to BC’s NP-PCCs are generally representative of the population from the clinics’ catchment areas. On average, rostered patients reported poor levels of accessibility to primary care services before joining one of the clinics. Conclusion: The NP-PCC model has been effectively reaching out to the patient populations for which it has been designed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".