Financial Resources Mobilization Performance of Rural Local Government: Case Study of Three Union Parishad in Bangladesh
Bibliographic record
Abstract
Union Parishads (councils) being the century old rural local government in Bangladesh are yet to fulfill the expectations of rural citizen which is mainly due to own resources constraints including miserable local resources mobilization. This paper focuses on Union Parishads recent revenue trend and performance from five years secondary data (2003 -2007) and primary data collected from Parishad representatives, local people, government officials and national experts. Finding of the study shows that despite revenue potentials, weak revenue administration, inadequate adjustments and assignments of local revenue sources including lack of union functionaries training become impediments on local revenue enhancement. Other finding of the study suggests that in the absence of valuation based tax assessment system, households housing pattern and literacy rate can be significant determinants in ascertaining annual average holding tax revenue while per capita household holding tax, remittances, agricultural land ownership, households having electricity connections can be used as significant variables to determine the taxpayers ability to pay holding tax.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".