Developing an implementation model to address food shortages in Matabeleland South Province, Zimbabwe.
Bibliographic record
Abstract
Matabeleland South Province has since 1980 to date been experiencing acute food shortages.Currently, it is the province with the highest number of food insecure people.The study recommends a bottom up approach, that is beyond ZimASSET, that addresses food shortages in Matabeleland South Province.The purpose of this study is to develop an Implementation Model to address food shortages in the Matabeleland South Province of Zimbabwe.The study employed the Grounded Theory approach utilizing a purely qualitative design.Purposive sampling of 200 stakeholders, that is expert and typical case sampling was the primary method of research.As the study was unfolding, a theoretical sampling was later employed.A confirmatory retrospective document review of food security documents from the Zimbabwe Vulnerability Assessment Committee and the Famine Early Warning systems Network was done.The Entitlement Theory by Sen Amartya, and the Systems Theory by Von Bertalanffy were utilised as the theoretical point of departure for the study.The study utilised Key Informant Interviews, Focus Group Discussion and Document Analysis to mine data.Data was analysed using the thematic approach.Major findings and results showed a disjuncture and dissonance within the Provincial Food and Nutrition Security Task Force approaches used to address the food insecurity situation in the province of Matabeleland South.The findings showed that, there is an implementation gap in need to be filled, and all stakeholders must apply a bottom up approach in addressing the problem of food shortages.The developed Implementation Model was validated by the stakeholders who participated in the data collection phase and endorsed the bottom up approach, which as intended, conveyed the community's views.The Food Security Implementation Model is forwarding the community development aspirations to a new level that leaves footprints on the development terrain with a pragmatist component of coming up with home grown solutions to the problem of food insecurity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".