Integrating Environmental Governance into Sustainable Urban Development in Bangladesh
Bibliographic record
Abstract
Environmental governance refers to the process of making environmental decisions, who makes them and how they are carried out. It includes formal and informal institutional arrangements for resource and environmental decision-making and management. This study examined the degree to which Barishal City Corporation (BCC) and Sylhet City Corporation (SCC), two divisional cities of Bangladesh, integrated environmental governance into sustainable urbanization. This study has collected data through questionnaire survey from 600 stakeholders (300 from each city corporation) along with key informant interviews from the government officials of the selected City Corporations. The study's findings show that environmental governance can pave the way to creating a sustainable city a reality. The ineffective enforcement of environmental laws and regulations, the lack of organizational coordination, responsibility, and responsiveness, and the deficiencies in resource mobilization are also identified as some of the few issues in this regard. This study argues that cities may be made sustainable by raising environmental awareness and changing the way of thinking of citizens and local government officials so that they believe everyone of them has a role to play in building a sustainable city. Creating sustainable cities cannot be legislated or decided: it must become a part of the life of every resident and organization in the city. The main drawback of this paper is that it only examines two of Bangladesh's twelve city corporations.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".