Bibliographic record
Abstract
Abstract Zimbabwe’s Fast Track Land Reform Program has attracted a lot of scholarly attention. While some scholars have argued that the process through which landless peasants reclaimed land was chaotic and violent, others have praised it for having been one of the most radical redistributive land reform programs in Africa. While these debates have dominated scholarship on land reform program in Zimbabwe since 2000, what has been lacking has been a historical analysis of the entanglement between land resettlement and struggles over restitution. Land restitution has been at the center of the land redistribution in Zimbabwe. In spite of the successes that the government has made in redistributing land, land restitution is the last frontier in the struggle over land. Ruins, ancestral graves, and sacred sites are important landscape features whose emotive presence and materiality enable communities to make land claims and counterclaims. Land restitution processes have been initiated in a variety of regional and country contexts. In former settler societies such as Zimbabwe, South Africa, Kenya, Canada, and Australia, indigenous populations have laid claims over land dispossessed under colonial rule. In post-conflict societies internally displaced people have also attempted to lay claims over land that they had to leave behind fleeing from violence. Further, where large-scale land deals have been unsuccessful or revoked through resistance land reclamation has also been instigated. Land restitution is concerned with restoring landed property to former owners. As compared to land redistribution, restitution is not concerned with ironing out of inequitable distribution of land to create a just future but with reestablishment of former rights based on principles of justice rather than equality. Restitution is therefore based on returning land to former owners who can prove claims. Land restitution is an elastic concept covering a range of processes designed to appease what are perceived as historical injustices around loss of land rights.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".