Respect from specialists: concerns of family physicians.
Bibliographic record
Abstract
OBJECTIVE: To explore potential solutions to the challenge of gaining more respect for FPs from other specialists. DESIGN: An original Web-based qualitative survey, from May 27, 2004, to January 5, 2005, involving 5 rounds. SETTING: Province of Alberta. PARTICIPANTS: A sample of 28 Alberta FPs of differing experience, locations, and types of practices. METHODS: Purposeful maximum variation sampling was used to identify a heterogeneous sample of FPs. The Delphi technique was used with an anonymous, iterative, Web-based survey to develop consensus among participating FPs. The first 2 rounds of the survey were designed to generate rich, thick descriptions of the rewards and challenges FPs experienced; the last 3 rounds were designed to refine this information and identify potential solutions and support that key organizations could provide. This information was collapsed into themes using thematic content analysis and reviewed by a working group; with input from the working group we decided to focus our analysis on the challenge of gaining respect from specialists. MAIN FINDINGS: Each round yielded an 86% to 96% response rate, from which 11 key challenges were identified including "respect from specialists." Suggestions of potential solutions to gaining more respect included the need to create and develop relationships between FPs and other specialists and to support each other's roles; to raise the profile of family medicine in universities and teaching hospitals; to change negative attitudes by promoting the expertise and role of family medicine to others; to demonstrate and maintain a comprehensive skill set; and to address intraprofessional inequities and provide appropriate incentives. Participants suggested roles that organizations could play; for example, universities and medical schools could avoid making negative comments about family practice, reward FPs involved in teaching, and decentralize medical education to provide more experience in community settings and environments that model interactions between specialists and FPs. Organizations could recognize and promote the role that FPs play in the health care system, seek their input into decisions involving primary care, and move toward equitable and fair remuneration. CONCLUSION: Perceived lack of respect toward FPs from some of their specialist colleagues might be reflective of issues that go beyond family physician-specialist interaction. Solutions will likely require the involvement of academic centres and other organizations.
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 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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".