Contemporary Discourses and Contestations around Pro‐Poor Land Policies and Land Governance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The meaning of land and land policies is diverse and contested across and within local and (inter)national settings. The phrase ‘land policy’, used to refer to all policies that have anything to do with land, may be convenient, but it masks the actual complexity of issues. Meanwhile, concern for ‘pro‐poor’ land policy has coincided with the mainstream promotion of efficient administration of land policies, leading to the concept of ‘land governance’. Such concepts have enriched discussion on land issues, but they also complicate further an already complex terrain. In response, this paper offers possible analytical signposts, rather than an actual in‐depth and elaborated analytical exploration of this terrain. It hopes to be a modest step forward and towards a better understanding of contemporary policy discourses and political contestations around land and land governance.
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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) | 0.000 | 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 it