Clashing Claims: Conflict and Violence as Unintended Consequences of Tenure Transformation at Enoosupukia, Kenya
Bibliographic record
Abstract
"In recent decades, violent conflict has become a metonym for Africa. Conflicts on the continent have manifested in a variety of forms, from civil wars between armies, as in Sudan, to communal violence between citizens, as in the Rwandan genocide. In Kenya, a relatively peaceful and stable country, periodic eruptions of violent conflict have occurred at the nexus of politics, ethnicity, and land. In three distinct periods, prior to independence in 1961, in the era of political liberalization between 1991 and 1997, and again after the most recent general election in 2007, violent clashes have pitted members of different ethnic groups co-resident on contested lands against one another resulting in death, injury, and displacement. But the complexities of local conflicts over land and the motivations of local participants to violence have been overlooked as the role and motivations of the elite have been the focus of attention. In this paper, I use one example of this type of violence, an ethno-political clash over land at Enoosupukia, which took place in October 1993, to examine how tenure insecurity and local conflicts over land rights factor into what has previously been understood as political violence. While recognizing the important part played by the politicization of difference and incitement by key members of the national elite, I argue that violence at Enoosupukia was a product of the propagation of multiple, incompatible institutions of land and resource governance through which competing claims to land have been voiced. The conflicts underlying violence are not merely a result of the uneasy co-existence of traditional notions of land as territory with modern notions of land as commodity, but rather an unintended consequence of state-supported efforts to transform tenure, from 'customary' communal tenure to 'modern' private property."
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".