Shrimp Cultivation and Coastal Livelihood: A focus on Bangladesh Coastal Vulnerability
Bibliographic record
Abstract
<p>Shrimp cultivation has spread out rapidly in coastal Bangladesh. Secondary literatures provides the evidence that to afford an alternative way of livelihood for the locals, shrimp cultivation extended widely throughout the coastal areas of Bangladesh. But, the extension of shrimp farming is unable to create work opportunity for the locals in true sense. In this research, by using a household survey, to know their basic demographic information, it is revealed that though 80% of the household heads main occupation is fishing and related works but only 0.71% of their main source of fishing is shrimp farm. Moreover, in-depth interviews and Focus Group Discussions disclose that shrimp cultivation of this village is controlled and retained by the rich and outside investors, not by the poor locals. This research discovered that man-made disasters, along with the natural disasters are equally responsible in generating vulnerability from shrimp cultivation.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".