Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The sugarcane harvesting practices of farmers pose a recurring problem of burning the sugarcane fields every year, leading to the release of PM 2.5, which is hazardous to health and a matter of concern for all parties involved. The objective of this research is to investigate the causes of sugarcane burning by farmers. Data is collected through participatory observation methods and group discussions with a sample group of farmers in the provinces with the highest incidents of sugarcane field fires, namely Nakhon Ratchasima, Kalasin, and Khon Kaen in the northeastern region of Thailand during the 2021/2022 production season. Content analysis techniques are employed to identify the reasons behind the behavior of burning sugarcane. The findings reveal that sugarcane burning has been a long-standing practice among farmers, and the prevalence of burning has increased due to a shortage of labor for sugarcane cutting. The available machinery for sugarcane cutting is insufficient and unsuitable for the farmers' fields. Farmers who burn sugarcane fields are aware of the health impacts and have benefited from the government's measures to address the issue of sugarcane field fires. However, it is observed that the quantity of burnt sugarcane still exceeds the government's target, because burning sugarcane is a cost-effective, convenient, and rapid method. It is found that penalizing farmers at a rate of 30 Baht per ton of burnt sugarcane and providing assistance at a rate of 120 Baht per ton of fresh-cut sugarcane does not sufficiently motivate farmers to change their sugarcane burning behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it