Bibliographic record
Abstract
The international community undertakes complex interventions in states emerging from war. These interventions include broad efforts to reform the political and institutional structures of the state. After the United Nations took political control of Kosovo in June 1999, it embarked on such a reform program, extremely ambitious in nature. This thesis examines the efforts to rehabilitate and reform the health sector. The immediate post-conflict environment in Kosovo was extremely chaotic. Hundreds of millions of dollars poured into the province, funding the operations of several hundred non-governmental organisations. The initial efforts of the international community in the health sector were focused on coordinating resources and the activities of these organisations. However, Kosovo' s health system was in clear need of widespread reform. The system had been devastated by years of neglect and months of conflict. A reform program was undertaken, with the objectives of establishing a primary care based system, increasing the quality of secondary and tertiary care, modernizing the public health system, and ensuring a cost-effective, equitable health system. By 2004, the reform program had largely failed to meet these objectives. This study examines the reasons that health reform was so difficult utilizing a combination of methods, i.e. a review of literature on peacebuilding, health and conflict, and health reform; analysis of the implementation of reform utilizing primary evidence such as policy documents and health data; and interviews with key stakeholders. Results show two important lessons for other post-conflict interventions. First, the reform program neglected building the capacity of government institutions. If the state does not have the capacity to implement reforms, the sustainability of the health reform process will be undermined. And second, the Kosovo reform program failed to build the foundation for reform before initiating ambitious projects to modernize the health sector.
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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 | 0.014 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".