Encroachment of Canals of Dhaka City,Bangladesh: An Investigative Approach
Bibliographic record
Abstract
Abstract Dhaka City has been suffering from many environmental problems including flooding, water logging and other related problems. Urbanization, which is occurring very fast and with larger magnitude in Dhaka, is the intrinsic reason behind these problems. High rate of urbanization causes extensive urban area expansion and as a result canals, wetland and other water bodies are quickly vanishing from the landscape. This study shows the present physical condition of the canals; identifies the processes of canal encroachment; represents the consequences of canal encroachment. 13 canals of 50 were surveyed; local people were surveyed to identify the impact and processes of encroachment. According to this study, canals of Dhaka city are under serious threat of extinction and require immediate recovery actions. Canals are being encroached in various styles and this study identifies five: unauthorized land filling, illegal construction over canal, expansion of slum, solid waste dumping, taking advantage of lack of awareness of local people as well as government agencies. However, this study also discusses the grave consequences of canal encroachment: increasing flood vulnerability, wane of ground water recharge area and ground water level, collapse of natural drainage system, loss of local ecology and biodiversity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".