Decentralization and immunization program in a single-party state: the case of the Lao People’s Democratic Republic
Bibliographic record
Abstract
BACKGROUND: The Lao People's Democratic Republic (Lao PDR), a lower-middle-income country, lags behind other Southeast Asian countries in immunization coverage for children under two years of age. The organization of health services is a key determinant of the functionality of immunization programs. However, this aspect, and in particular its decentralization component of the healthcare system, has never been studied. METHODS: A case study in the Lao National Immunization Program was performed using a neo-institutional theory-based conceptual framework, highlighting the structure (rules, laws, resources, etc.) and interpretative schemes (dominant beliefs and ideas) that underlie the state of decentralization of the healthcare system that support the conduct of the immunization program. Twenty-two semi-structured interviews were conducted with representative actors from various government levels, external donors, and civil society, in four provinces. Data were complemented with information retrieved from relevant documents. RESULTS: The Lao healthcare system has a deconcentrated form of decentralization. It has a largely centralized structure, albeit with certain measures promoting the decentralization of its immunization programs. The structure underlying the state of centralization of immunization services provided is coherent with a shared dominant interpretive scheme. However, the rapid economic, technical, and educational changes affecting the country suggest that the coherence between structure and interpretative schemes is bound to change. CONCLUSION: Unprecedented opportunities to access quality higher education and the use of social networks are factors in Lao PDR that could affect the distribution of responsibilities of the different levels of government for public health programs such as the National Immunization Program.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".