Women's rights to land in Tanzania: Does village land use planning strengthen women's land rights?
Bibliographic record
Abstract
Based on a scoping review of the literature, we examine whether village land use planning (VLUP) in Tanzania strengthens women's land rights, as measured by women owning Customary Certificates of Right of Occupancy (CCROs) as individuals, or jointly. The review highlights significant variations in the outcomes of VLUP processes for women. While some projects show high levels of CCROs ownership by women, in many cases there are obstacles to them claiming their rights and receiving the document. Key challenges include limited participation of women in VLUP processes, limited female representation in village institutions, the costs of CCRO applications, patriarchal norms, and household power dynamics. Some civil society organizations have improved women's participation in VLUPs, and developing village bylaws has proven effective in reducing gender disparities in land ownership and improving women's representation. Despite these initiatives, challenges remain, such as women's reluctance to increase their already significant labour burden with unpaid voluntary positions, and social norms limiting their participation in meetings. External organizations have also introduced cellphone-based applications or remote sensing data to facilitate the collection of data and resolution of disputes. However, these technological solutions require supportive training and a favorable socio-cultural environment to be effective. We conclude that while VLUP processes have potential for securing women's land rights, in many cases men may benefit at the expense of women, unless significant investment is made in ensuring gender equity. The marginalization of pastoralist communities and ethnic minorities in VLUP may also need attention in some cases. The government of Tanzania is encouraged to collect data on women's land rights to report on progress towards SDG goal 5a and ensure women's economic empowerment through land rights.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".