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Record W2111824963 · doi:10.1177/229255031101900107

Supply Side Economics – the Canadian Way

2011· article· en· W2111824963 on OpenAlexvenueaboutno aff
John Robert Taylor

Bibliographic record

VenueCanadian Journal of Plastic Surgery · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careRecessionMedicineControl (management)EconomicsEconomic growth

Abstract

fetched live from OpenAlex

We tend to think of economics in health care as supply and demand, similar to buying a car or shopping in a store: enough demand and lower prices, produce supply. This is not the case in our health care system. Our system is a supply system, and the supply is controlled. In controlling the supply, we control the cost, so we keep prices the same. In a recession, it is advantageous for the provider. This has merits as we look with pride at our system, which keeps costs down, compared with a much higher cost system in the United States. The supply system is a very Canadian idea. It is like our milk marketing board or the wheat board that is meant to stabilize prices for producers. The price of health care in Canada is apparently 9.1% of the GDP and, rhetoric aside, achieving this percentage is the real reason why our medicare is structured the way it is. However, as surgeons, we are affected much more than general physicians. General physicians can increase their income by seeing more patients; however, we are more limited by restricted operating times, which have been cut back to meet annual hospital block funding limits. There is a demand system as well; however, it has been altered by the new policies. All urgent treatment, emergency heart therapy and cancer care takes precedence over nonurgent cases and increases their wait times. In a restricted system, some treatments must wait; the longer the wait, the less you spend now, or at least that is what is reflected in the books. You need a big bureaucracy to make this happen because you need volumes of information to be forewarned of any restiveness and to fix it early. A supply system to control costs makes it predictable for employers to do business. However, it is also necessary to consider the demand system and its benefits for supplying services without too many consumer complaints, which could lead to political instability and demand for change. The demand system has been eliminated; however, not entirely. The demand system keeps popping up because it is so inherent in human nature. Suppose you can’t get something, at least for a long time, you will go somewhere else where that service is available. This is encouraged by the system managers because it means only one centre of excellence needs to be built because duplication is expensive. The problem then arises when that centre becomes overbooked and refuses referrals. Having a supply system protected by a monopoly means continued awareness of the benefits of a demand system. But because the demand system now does not work naturally, you have to simulate it: you have to predict demand rather than responding to it as it occurs. So, the number of managers has to increase. In a closed budget system, this leaves less money for those providing services. Strangely, none of the recipients of services need to know about any of this because it is hidden and delegated to those whose job it is to run everything. The fascinating thing is that despite complete system control, health care costs are increasing and now account for 40% of provincial budgets. Why? This increasing cost is what medicare was supposed to control. I wonder what will happen next.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0160.018
Scholarly communication0.0210.009
Open science0.0020.005
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0390.004

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 head0.093
GPT teacher head0.206
Teacher spread0.113 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2011
Admission routes2
Has abstractyes

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