Changing Rural Power Structures Through Land Tenure Reforms: The Current Dismal Role of International Organizations
Bibliographic record
Abstract
Agricultural or rural development, although generally considered to be a process to improve the economic and social conditions of poorer groups in rural areas, signifies different things to different people. The meanings vary in terms of priorities to be considered, the means needed to achieve the set goals, and how the principal actors should co-operate. This paper examines the role of leading international agencies in sponsoring land tenure reforms—a role which had vanished from the development agenda in the 1980s and early 1990s, but which has resurfaced in recent years thanks to actions by national and international civil society organizations and to grassroots mobilizations. Promoting reforms in land tenure institutions and relations is key to reducing rural disparity and improving food security, income and family welfare among marginalized rural population groups. But modifying a rural power structure to promote the interests of the poorer and weaker segments of the rural population is a complex process, and the international organizations included in the analysis have focused their activities on less politically sensitive, subsidiary issues, leaving existing rural power structures and relations largely unimpaired. The paper is based mainly on secondary material, combined with primary information and the author's observations of a number of ongoing land reform initiatives.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".