Farmers' Knowledge of Land Degradation Issues in Ganga District, Daura Emirate, Katsina State, Nigeria
Bibliographic record
Abstract
The study described here examined farmers' knowledge about land degradation; their understanding and interpretation of factors related to soil fertility decline; their responses to land degradation; their views on the seriousness of the problem; how their perceptions influenced the management practices of their farmlands within the study area; variations in farmers' perception of land degradation / soil fertility decline across Ganga District (Ganga, Godai, Shadambu, Tambu, and Mazoji); and the influence of level of education, gender, and age on farmers' perceptions of land degradation / soil fertility decline issues in Ganga District of Daura Local Government Area, Katsina State. A total of 240 semi-structured questionnaires were administered to respondents within the study area, supplemented by oral interviews and field observations. Purposeful sampling technique was used to select famers actively involved in farming practices in the area. The farmers were surveyed between December 2008 to January 2009,...
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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".