Knowledge and Innovations for farmers from Teaching Agriculture in Ugandan Primary Schools: A Study of Kumi Communities in the Teso Sub-Region
Bibliographic record
Abstract
Kumi communities consist of Bukedea, Kumi and Ngora districts whose agriculture is increasingly complex with declining productivity because of population increase, climate change, low yielding technologies used & poor market access impacting negatively on yields and environment. More knowledge & innovations are needed by farmers. Teaching agriculture in primary schools raised hopes, hence the study. The design was exploratory. In-depth interviews, focus group discussions, questionnaires, documents and observations were used to collect data from 40 primary schools randomly selected. Of 2,069 respondents, 1,951 were head teachers, teachers and primary seven students & 118 were farmers including extension workers purposively selected. Qualitative data were analysed using open coding & axial coding based on objectives and research questions. Agricultural productivity and its growth rate were found low caused by many factors. Education quality and innovations attained by farmers were not assuring for successful farming and rural living. Primary school agriculture was poorly conducted encountering implementation problems such as limited land, no funds, unfavourable weather and lack of improved inputs. Forty five percent (45%) of the students preferred farming as an occupation. The key innovations attained were literacy and numeracy important in the use of improved inputs; knowledge and skills for several farm operations including environmental management and good family living. On ranking school completion rates and farm output of 16 sub-counties, Spearman Rank Order coefficient computed was positive (r = 0.421 with r2 = 0.1772, 18% at 0.05 α). Increased farm output was explained by 18% through completed primary education by farmers. Smallholder farms in Kumi for years may only be run commercially through intelligent and differentiated policies, addressing market access, jobs in non-farm economy and social transfers to improve welfare of the poor. Primary school agriculture through innovations attained by farmers enhances production thus the need for more investment in it.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".