Sustainability of agricultural systems in the coastal zone of Bangladesh
Bibliographic record
Abstract
Abstract Transformations of the agricultural systems have been taking place in the coastal zone of Bangladesh. In different settings, farmers have become involved in massive shrimp cultivation, shrimp–rice cultivation, rice-based improved agricultural systems or shrimp–rice–vegetable-integrated systems. The long-term livelihood, food security and adaptation of the coastal people largely depend on the sustainability of these agricultural practices. In this context, assessing the level of sustainability is extremely important. The present study attempts to examine the sustainability of agricultural practices in the coastal zone of Bangladesh. A field study was carried out in fiveupazilas(counties) in the coastal zone. The data were collected through in-depth questionnaire surveys, focus groups discussions, field observation, key informants and secondary materials. A comprehensive suite of indicators was developed considering productivity, efficiency, stability, durability, compatibility and equity related to the coastal agriculture. The categories and the indicators were aggregated using Multi-Criteria Decision Analysis to measure the sustainability level of five study sites. The integrated agricultural system (shrimp–rice–vegetables) of Dumuria appeared to be the most sustainable system among agricultural practices, and other integrated systems (rice-based) of Kalaroa were also found to show a good level of sustainability. The massive shrimp cultivation system of Shyamnagar and Kaliganj appears to be the least sustainable. A traditional agriculture system with some improved methods followed in Bhola Sadar also performed in a satisfactory manner. Measuring agricultural sustainability in this way produces a useful summary of sustainability issues. The information generated from the study may be used in formulating policies for this part of the country. The holistic and interdisciplinary approach employed here has the potential to a useful framework for sustainability assessment.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".