Study on Comparative Assessment of Aquaculture Technology Adoption by the Carp, Golda and Bagda Fishers in the Sidre Affected Area of Bangladesh
Bibliographic record
Abstract
The study was carried out in November 2102 to assess the comparative assessment of aquaculture technology adoption by the Carp, Golda and Bagda fishers in the Sidre affected area of Bangladesh. The study was done under the Emergency 2007 Cyclone Recovery and Restoration (ECRRP) Project (Component-A) with the help of staff of Shakoler Janny Kallyan, Non Government organization (NGO). There were three types of respondents (Carp, Golda and Bagda Fishers). The summery findings of the study are described in this section in briefly. It is found from the analysis that 100% of the Carp fishers indicated to have adopted at least one new aquaculture technology disseminated by the project for improved carp fish culture in the ponds. 31.5% of the Carp fishers indicated to have adopted 4 types of new technologies (the list of the new aquaculture technologies were identified by the project expert and DoF field officials) while 20.3% adopted five types of new technologies. The 100% of the Golda fishers adopted at least one new technology disseminated by the project for improved Golda shrimp culture. 95.5% adopted the technology named “improved Pond/Gher preparation” while the adoption rate of female fishers (98.1%) is higher than in male (94.9%). 100% of the Bagda fishers adopted at least one new technology disseminated by the project for improved Bagda shrimp culture in Ghers/ponds. The second highest number of fishers (88.85%) adopted the technology of “use of supplementary fish feed” while the lowest number of fishers (48%) adopted the technology “maintaining proper shrimp post larvae stocking” from the five disseminated new technologies by the project.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".