Development and the Environment: Overview of the Development Planning Process in Agricultural Sector, in Uganda
Bibliographic record
Abstract
The social component of the environment associated mostly with human activities has significantly imposed a threat to the only life-support systems of the earth. Uganda made adjustments in its planning process to prioritize environment conservation. However, in the recent past years, mostly between 2013 and 2017, the country stretched its resources to increase agricultural production, both livestock and crops. The objective of this study was to establish and document the development and the environment conservation strategies at global and regional levels with an overview on the development planning process in agricultural sector, in Uganda. The results showed that the sustainable development plans with participatory approach at international, regional, national and local or community levels are the best methods to cope with and reduce the negative impacts of man’s activities on the environment. The understanding of the complexes of the environment is very important to ensure the relationship between the social, economic and environmental protection for a sustainable development. The results also indicated that in Uganda, the agriculture industry made consistent efforts to increase agricultural production by 431,161 hectares and livestock heads by 7,878,000 (cattle, sheep, goats, pigs, and poultry) between 2013 and 2017. This increased agricultural greenhouse gas emission due to the use of synthetic fertilizers, burning of the cleared grasses, and use of manures applied to boost soil fertility and the reduction in the trees that sequester CO2. This study recommended that the agricultural sector should opt for sustainable agriculture by adopting practices like use of multipurpose crops that can offer environmental services like binding soil particles together to control erosion as well as yielding more food products. Dual-purpose livestock breeds should be adopted to avoid immense numbers that serve different purposes that will probably lead to increased GHG emissions.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".