Bibliographic record
Abstract
Background Whole person care has been a foundation of the modern practice of family medicine, and therefore one might expect that such an approach by family practitioners would evolve and mature over time. Some of these clinicians, however, currently question their ability to provide such holistic care because of external factors they perceive as negative, and over which they have little or no control. Objectives This presentation will explore perceived inhibiting factors affecting family doctors ability to provide whole person care within the publicly-funded health care system of the Canadian province of Quebec. Method The presenter, an academic and clinician scientist with forty-four years of experience practicing family medicine, will present personal perspectives, along with those gathered informally from a broad cadre of colleagues working in different settings. Using the idiom of “elephant in the room” to identify problems or obstacles that may not be voiced, this talk will start with consideration of elephant anatomy as being comprised of thirteen distinct anatomical parts that contribute to a functional whole. An analogy will be developed in which thirteen distinct factors are presented as likely impeding or discouraging whole person care by family physicians. Conclusion Some agendas and policies of health care planners and administrators, either alone or collectively, and intentionally or unintentionally, may decrease opportunity or ability of family physicians to provide whole person care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".