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Record W2407333414

Pulse: Net earnings for FPs, specialists

2002· article· en· W2407333414 on OpenAlexvenueaboutno aff
Lynda Buske

Bibliographic record

VenueCanadian Medical Association Journal · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentNet incomeEarningsFee-for-serviceOverhead (engineering)Service (business)MedicineBusinessFinanceHealth careComputer scienceEconomicsMarketing
DOInot available

Abstract

fetched live from OpenAlex

The Canadian Institute for Health Information (CIHI) has just released information on average fee-for-service payments for physicians who received at least $50 000 in such payments from a provincial medicare plan in 1999/2000. Since these figures are based on gross fee-for-service payments, the CMA has used overhead information collected in its annual Physician Resource Questionnaire (PRQ) to estimate average net professional income earned from these payments. Estimated overhead is an average of figures reported by survey respondents, some of whom are paid primarily via fee-for-service payments, plus others who are not. The 1998 PRQ results indicated that overhead expenses for physicians averaged 32% of gross income, ranging from an estimated high of 36% for family physicians to 28% for specialists. When the PRQ results are applied to the CIHI data, estimated 1999/2000 average net incomes from fee-for-service payments (before taxes) were $119 872 for FPs and $178 906 for specialists. Results for the 1998 PRQ survey are accurate within ±2.2%, 19 times out of 20. — Lynda Buske, Associate Director of Research, CMA

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0960.032

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 head0.035
GPT teacher head0.246
Teacher spread0.211 · 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
Published2002
Admission routes2
Has abstractyes

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