Bibliographic record
Abstract
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 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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.
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".