Bibliographic record
Abstract
Similar to some other countries, the lack of proper certification systems creates significant problems in identifying real organic products in Sri Lanka as well. Therefore, the present study aims to investigate the current situation of organic certifications used by farmers in two selected districts of the country which are having high potentials for organic agriculture. Initially, a literature review was conducted to find out the present situation of organic product certification in the world and in Sri Lanka. This was followed by a field survey conducted from March 2017 to December 2018 using 300 randomly selected farmers. The data were analyzed by descriptive statistics. According to the literature review findings, some developed countries such as USA, Canada, New Zealand and Australia etc. carry out organic certifications in a well-organized manner. Meanwhile, seven international organic certification agencies are operating mainly for export products in Sri Lanka. However, currently only four certification systems are functioning for the local market products. As per the field survey findings, out of four, only two certification systems are used in these areas. While few farmers (2.3%) use the “Participatory Guarantee System” (PGS) and very few farmers (1.3%) use “SriCert” certification. However,most farmers (49.7%) are willing to shift towards organic agriculture and adopt organic certifications in future. Challenges such as the doubt about a reduction in harvest and income from organic farming, lack of market opportunities for organic products, low level of awareness of certification process, high cost and complexity of certification process are acting as barriers. Therefore, the development of user-friendly certification procedures and awareness programs for the potential farmers and initiating marketing facilities for certified organic products will motivate farmers towards the certification of organic products.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".