Bibliographic record
Abstract
OBJECTIVE: To understand physician acceptance of new patients, specifically the use of "meet and greets"; and to explore FPs' rationale, beliefs, and processes regarding these appointments. DESIGN: Exploratory qualitative interviews. SETTING: Nova Scotia. PARTICIPANTS: A purposive sample of 12 FPs who had previously participated in the Models and Access to Primary Care Providers in Nova Scotia study. METHODS: In-depth, semistructured, 1-on-1 qualitative interviews. Interview transcripts were coded using Atlas.ti and analyzed for typologies and common themes regarding accepting practices. MAIN FINDINGS: Four typologies of accepting practices emerged: no form of meet and greet; nonscreening meet and greet to gather a history; meet and greet to assess alignment of patient needs and provider scope; and meet and greet to screen out undesirable patients. Typology 1 was subdivided: accepting first-come, first-served and accepting with previous patient knowledge. Rationale for each varied. Family physicians employing typologies 1 and 2 emphasized the importance of equitable access to primary care. Family physicians employing typologies 3 and 4 highlighted the challenges of meeting the needs of specific populations within the context of professional and systemic constraints. CONCLUSION: Meet and greets before accepting new patients are purposed differently across providers. Some FPs incorporate these meetings ethically; others present challenges to the principles of equity and nondiscrimination. Policy implications exist for how providers admit new patients and what resources might support more equitable access.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".