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Record W1153128332 · doi:10.20381/ruor-9720

Primary care practice in Ontario: An analysis of the factors that affect physician supply and activity

2004· dissertation· en· W1153128332 on OpenAlexaboutno aff
James G. Donnelly

Bibliographic record

VenueuO Research (University of Ottawa) · 2004
Typedissertation
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)Primary careMedicineFamily medicineNursingBusinessPsychologyGerontologyCommunication

Abstract

fetched live from OpenAlex

Health care reform is an essential and continuous process as a nation's medical system adjusts to meet changing needs in the population. It has been recognized that the Canadian health care system is in need of revolutionary change. Many other countries have had similar experiences to Canada in both resource shortages and reform process. The population of Ontario is growing and becoming older. Older persons place greater demands on the health care system. At the same time the Ontario physician workforce has decreased in size, increased in age and has more female entrants. Elderly physicians reduce their workloads as they reach the age of 65 years. Female physicians take on lower workloads than male physicians, especially in the early part of their careers. Over the past eight years there have been less entrants to Family Practice and more to specialty services. As well, in the past five years nearly 60 percent of Family Practice physicians have reduced their scope of care by limiting their practices. Taken together these observations demonstrate that while there is an increased need for primary and secondary care physicians there has also been a concurrent reduction of the number of physicians both in terms of census and also in terms of workload. In the past decade the Universities of Ontario have increased tuition fees significantly with respect to the other provinces. Financial pressures and control of hours (lifestyle control) may further limit the intake of post-graduate Family Practice physicians. Reversing these trends will require increasing the physician workforce and the development of programs to encourage entry into primary 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.078
GPT teacher head0.431
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2004
Admission routes1
Has abstractyes

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