Decentralization in Public Health Systems: Analyzing the Decision Space and Opioid-Related Response in Edmonton Zone and Ottawa Public Health
Bibliographic record
Abstract
This thesis explores how decentralization shaped the organization and function of public health systems in Canada through the comparison of Alberta and Ontario. Decentralization has been widely promoted as a way to increase responsiveness and local engagement in health systems broadly, while centralization is often seen as a means to improve coordination and efficiency. Several Canadian provinces have been pursuing centralization reforms in their health systems and the variation in public health systems across the provinces provides an opportunity for comparative analysis and learning. A comparative case study design was employed, focusing on Edmonton Zone (Alberta Health Services) and Ottawa Public Health as representative local public health units functioning in one system characterized as centralized (Alberta) and one as decentralized (Ontario). The Decision Space Analysis was used as an analytical framework to assess decentralization in both cases across key health system functions from 2011 to 2023. The opioid-related crisis served as a tracer for this study, adding another layer of focus to the data collection and analysis to explore how decentralization as a structure is related to public health responses. Data collection involved 41 documents and 10 key informant interviews for the Alberta case, and 45 documents and 9 key informants for the Ontario case. Content and thematic analysis techniques were used to conduct the Decision Space Analysis across health system domains such as financing, service organization, human resources and governance, and inductive analysis techniques were used to better understand how decentralization was experienced in general and for the tracer. Ottawa Public Health generally exhibited wider decision space than Edmonton Zone and differences emerged in areas of human resources and governance. However, the two local public health units also demonstrated similarities and overlap in areas of finance and service organization. Despite structural differences, both jurisdictions saw the implementation of comparable responses to the opioid-related crisis with some differences in approaches to safer supply programs. The potential reasons for these similarities and differences are explored. This study contributes to public health systems and services research by advancing a more nuanced and function-specific understanding of the structural arrangements in Alberta and Ontario’s public health systems, moving beyond simplistic dichotomies of centralization and decentralization. The utility of the Decision Space Analysis, both as an analytical framework and a way to understand policy debates, is also discussed.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".