It's Your Responsibility: The Socioeconomic Implications of Home-Based Renal Care
Bibliographic record
Abstract
Medical research has demonstrated that End-Stage Renal Disease (ESRD) is one of the most cost-consuming and labour-intensive chronic diseases. The frequent and perpetual need for dialysis treatments has created a crisis in renal care that has challenged health care systems to meet the current and future needs of the population. The crisis response in Ontario, Canada has relied upon the principles of neoliberalism to implement a home-based model of care that shifts dialysis from the hospital to the home. This transfer of treatment involves a significant downloading of work and costs to the patient, but offers them better health outcomes and autonomy over their care. To understand the socioeconomic outcomes of home dialysis programs, this dissertation draws upon interviews with patients, care partners, and frontline health care professionals to explore: 1) how home dialysis programs implement neoliberal processes of responsibilization which result in patients and their families performing their own care; and 2) how patients and their families respond to this responsibility within the context of their household. Major findings reveal that patients and their families experience significant hardships when transitioning to home-based care as they must negotiate divisions of labour within the family while managing the emotional and economic costs of treatment. In spite of these hardships, patients gain a significant amount of agency within the health care system upon their enrollment. Rather than being passive recipients of downloaded work and costs, they actively manage their care by directing the actions of frontline health care professionals, and influence wider care practices at the program level.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".