Constraints to Women Smallholder Farmers’ Efforts in Ensuring Food Security at Household Level: A Case of Msowero Ward of Morogoro Region Tanzania
Bibliographic record
Abstract
Women smallholder farmers (WSFs) play great roles in ensuring food security at household level as a poverty reduction strategy, but they are faced with a number of constraints that deprive them from fulfilling their potential as farmers, food producer, provider and entrepreneur. In evaluating the constraints on WSFs toward ensuring food security at household level as a poverty reduction strategy, this study focused on examining variables such as the women’s level of education, access to resources, technology, family size, as well as the agro-inputs. The results showed that 58% of respondents were food secured, while 42% of the respondents were food insecure. Also more than 60% of smallholder farmers in the study area are women, though their efforts and the mechanization of agriculture has marginalized them, and women are more considered as consumers than producers. Morever, WSFs have been less appreciated and continue to suffer from limited access to resources and opportunities especially in agriculture sector. A Logistic regression analysis showed that five out of eight variables analyzed were significant at the 5% level (p < 0.05), However, to ensure that research results are utilized and WSFs have access to new irrigation service technology, markets, education, capital, farms, as well as the agro inputs, the government and public and private development sector have to support and integrate short and long-term development initiatives and make sure that the initiatives are conceived and implemented with special consideration of women as smallholder farmers.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".