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Record W4391329361 · doi:10.26443/ijwpc.v11i1.401

Anatomy of the elephant in Quebec family practice

2024· article· en· W4391329361 on OpenAlexaffvenueabout
Mark J. Yaffe⃰

Bibliographic record

VenueInternational Journal of Whole Person Care · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsMcGill UniversitySt Mary's Hospital Centre
Fundersnot available
KeywordsAnatomyMedicineFamily medicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.341
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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