Environmental Impact of Poultry Waste Management Practices in Jhenaidah, Bangladesh
Bibliographic record
Abstract
The poultry industry is one of the major agricultural sector which contributes to the economic development of Bangladesh. Improper poultry waste management practices causes environmental pollution and also public health hazards. Our study assessed the biosecurity measure and poultry waste management practices of 35 poultry farms in Jhenaidah Sadar Upazila, Bangladesh. Data were collected by the questionnaire from the poultry farmers. Our focusing on farmers demographics, farm characteristics, sanitation, and waste disposal practices. The results revealed that most farms were run by middle-aged, educated males. Around 77% of the owners lacked formal training on waste management. Poultry waste was predominantly disposed of on roadsides (62.85%) or in pits (37.14%). Waste was repurposed as manure (45.71%) or fish feed (22.85%) by some, but biosecurity measures remained inadequate. Complaints of noise and odour pollution were commonly reported by neighbours. Continued mismanagement led to practices of improper disposal, despite sporadic attempts at cleaning and disinfection through methods such as calcium oxide or potassium permanganate. Poultry waste can be utilized for composting or for biogas production to support environmental protection and public health.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".