Analyzing family planning expenditure in Bangladesh
Bibliographic record
Abstract
Background The study conducts a family planning spending assessment to identify the resource gap for attaining family planning goals of Bangladesh’s 4th Health, Population, and Nutrition Sector Program (HPNSP). This study is motivated by the paucity of published literature on tracking family planning spending, especially in the Asian context. The study aims at tracking family planning spending from government sources by the agents, providers, service categories, and inputs of family planning services in Bangladesh. Methods We utilized a modified version of the National AIDS Spending Assessment (NASA) methodology to track family planning spending incurred by the government during the fiscal year 2018-19 (July 2018 to June 2019) and the equal period of 2019-20, focusing on the contraceptives. Results The total family planning expenditures were US$262.90 million and US$229.00 million in the fiscal year 2018-19 and 2019-20, respectively. The Directorate General of Family Planning (DGFP) managed a major share of the available family planning funds (93.4% and 90.1%, for two investigated years), while the Upazila Family Planning Office (UFPO) acted as the primary service provider, with over half of the resources spent. Salaries and allowances constituted the largest share of all costs (60.6% and 61.0%), while monitoring, evaluation and research amounted to an almost negligible share. Conclusions The findings of this study warrant an increase in the family planning funds to reduce the unmet need and discontinuation of the current family planning methods. Future studies should explore the whole gamut of family planning spending by including the share of development partners, NGOs, and out of pocket payments.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".