Reporting immunization coverage inequalities in Pakistan
Bibliographic record
Abstract
BACKGROUND: Immunization coverage in Pakistan is unequally distributed. Understanding the current status of reporting of immunization coverage inequalities in Pakistan can help to identify gaps and opportunities for strengthened monitoring and reporting. AIMS: To assess the published literature on immunization coverage inequality measurement and reporting in Pakistan. METHODS: We performed a literature search in PubMed in April 2019 to obtain articles reporting inequalities in immunization coverage in Pakistan. A data extraction rubric was applied to collate information about data sources, immunization indicators and dimensions of inequality. RESULTS: We included 42 studies in our analysis. Most studies reported data from household surveys or research studies. Dimensions of inequality reflected geography (primarily provinces/territories), economic status, place of residence, education level, sex and occupation. District-level comparisons were featured in 5 studies that were subnational in scope. CONCLUSIONS: Expanded monitoring at district level is warranted as a major way forward in characterizing immunization inequalities in Pakistan.
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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 | 0.023 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".