Bibliographic record
Abstract
This dissertation consists of three independent essays addressing three separate health care policy issues.Essay 1, "Incentive Effects of Government Mandated Cost-Shifting," shows how mandated cost shifting, because it does not require resources to pass through the hands of government, can be an optimal form of income redistribution in providing health care to the poor of society when government is sufficiently costly.Under this system, the government mandates the proper treatment of illness regardless of ability to pay and enforces that mandate with investigation.The paper shows that under costly information on illness the physician cheats by providing the wrong treatment when treating a rich patient who has low severity illness and a poor patient who has high severity illness.In response the government also investigates the treatment of such patients.The paper also shows the conditions under which mandated cost shifting is less wastehl and beneficial to patients.Essay 2,"The Effects of the Relationship between Quantity and Quality of Care on Quality of Care," shows that the relationship between quality and quantity in the patient's utility as well as in the cost of care play an important role in determining the ability of a payment scheme to induce efficient quality and quantity of care.The payment schemes examined are fixed fee for service, prospective payment, and cost sharing.The paper shows that neither prospective payment nor fixed fee for service can be used to induce a first-best provision of quality and quantity.Cost sharing is the only scheme that can be used to induce the efficient supply of both quantity and quality.Essay 3, "The Effect of Hospital Downsizing in British Columbia on the Quality of Care for Maternity Patients" uses maternity data from the Canadian province of British Columbia to estimate the effect of the reduction in hospital utilization rates and the transfer of care from hospitals to communities and to patients7 homes on readmission rates.The results show that the policy reduced hospital length of stay and increased readmission rates for maternity patients.DEDICATION To Jesus Christ, my Love, who means more than this world to me.To my parents and Archbishop P. Sarpong, for continuing to believe in me.faithfulness.Starting with the members of my committee, I would like to acknowledge those who were God's instruments in making this thesis a reality.Gordon Myers has been the stronghold of this thesis.His encouragement has been invaluable.He valued the idea in the first essay and encouraged me to pursue it.Working with him has really deepened my understanding of economic theory and modelling.This deepened understanding is also partly due to Nicholas Schmitt, whose financial support and dedication to the second chapter made an impression on me.Jane Friesen also helped to improve my empirical skills.This is very much appreciated.I also would like to acknowledge the Knowledge
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".