Workers' Compensation Boards and Nineteenth Century French Railway Firms
Bibliographic record
Abstract
WCBs are able to provide fast access to high-quality healthcare to workers through their role as parallel payers in a publicly financed healthcare system. On the positive side, added funding from WCBs may help public facilities to fund and keep costly medical expertise. On the negative side, WCBs may drive them to accept much-needed funding below true costs of care and to crowd out public-pay patients. Some studies showed that governments were expecting from policies supporting parallel private payers the benefits hoped for by Hurley et al, while some of their negative effects could not be avoided. The combination of cost shifting from public-pay to private-pay patients, and of crowding out, are the ingredients of a Dupuit's case wherein third-class passengers riding the nineteenth century French railway system were subsidizing first- and second-class passengers. With the pressure for allowing private financing of healthcare throughout Canada, the Canadian healthcare system may be ripe for a ride toward subsidization of private-pay patients by the public purse, with a little help from WCBs.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.052 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".