The need for community inclusion in water basin governance in Bangladesh
Bibliographic record
Abstract
In this paper we focus on the principle of community inclusion in water and ecological resource governance and document the negative impacts of its absence, in Chapra village, Bangladesh, on sustainable development and livelihood security. This community depends heavily on common property resources such as wild plant foods, fish and ‘natural’ crop fertilizers derived from river siltation and other sources. For the vast majority of people in Chapra, these common ecological resources create the ability to effectively match livelihood strategies to the conditions of both dry and rainy seasons. However, this socioecological livelihood pattern is increasingly undermined by the hydropolitics and top–down water management practices that prevail throughout the Ganges–Brahmaputra Basin in Bangladesh. These practices lead to ecosystem failures and ecological resource degradation which in turn cause survival challenges for the marginalized people who constitute the vast majority of the population. In this paper we explicitly seek to answer the question: how might community inclusion in governance processes help protect ecological integrity and common property resources and thereby support an alternative and more sustainable form of development for the region? In order to answer this question we first document the nature of livelihood practices in Chapra, based on 1 year of fieldwork, and then outline the mismatch that now occurs between livelihood practices, ecological characteristics and governance practices. We conclude with the argument that greater community inclusion in governance must be part of the solution to existing problems and we propose specific governance reform measures to facilitate community inclusion.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| 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".