Revenue Mobilisation Performance of Union Parishad in Bangladesh: Is It Convergence of Central-Local Relations?
Bibliographic record
Abstract
Despite several local revenue sources, Union Parishads (Councils) in Bangladesh are yet to perform optimal local revenue mobilisation. This paper evaluates Unions revenue trend and performance, budget and planning practices, effect of central grants on local revenue in the backdrop of central government recent initiative for Unions capacity building. Analysis includes three representative Unions, in a comparative perspective, and uses secondary and primary data (from Parishad functionaries, local citizen, government officials and national experts). Findings show that open budget discussion, discretionary and performance grants have positive impact on local revenue collection while this study raises question about sustainability of the revenue augmentation due to disparity of deconcentrated allocations system and feeble local democratic governance. Study recommends making adjustments in local revenue shares, increase discretionary grants, and validation of local participatory governance. This study has implications for local revenue mobilisation through convergence of central-local policy and strategy, specially for developing countries having similar local socio-economic and revenue source footings.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".