Livelihood Resilient Strategies through Beekeeping in Chitanga Village, Mwenezi District, Zimbabwe
Bibliographic record
Abstract
The study sought to establish the contribution of beekeeping in rural livelihoods sustainability. Chitanga village had experienced low agricultural productivity due to poor and infertile soils and this has led to food insecurity which had driven them into beekeeping. This opportunity has been driven by the existence of tall trees and wild plants that develop flowers in the village which attracted bees. However, the utility of beekeeping enterprise as a livelihood activity has not been fully realised. This study was carried out in the context of a sustainable rural livelihoods framework. This framework states that at any given time, every community or society falls under a vulnerability context as a result of both natural and human made disasters. In light of the vulnerability, a community mobilises the various forms of its assets at its disposal to earn a living. Applying this framework, the study analysed the strategies the community employed to enhance its livelihoods through the sharing of benefits. The research used questionnaires, structured interviews and observations as sources of gathering data. The study established the benefits which accrued from beekeeping that included honey as food, income in the form of cash, medicines, scenery creation for tourism and income generating projects through making of hives, growing of flowers and citrus fruits which attract bees. A backward and forward linkage of enterprises emerged. Employment creation and increasing in the number of livelihood activities in the area has been witnessed due to beekeeping. This culminated in diversification of livelihood options leading to rural transformation through utilization of local available resources. The study recommends that the sustainability of beekeeping enterprise should be reinforced by backward and forward linkages. The government partnered by NGOs should take the lead and compliment the efforts of beekeepers by providing clear policy and planning.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".