Clashing Claims: Neopatrimonial Governance, Land Tenure Transformation, and Violence at Enoosupukia, Kenya
Bibliographic record
Abstract
This article revisits a case of violent conflict at Enoosupukia, Kenya, in October 1993, that has previously been analyzed as a clear example of top-down, elite manipulation of neopatrimonial domination. Drawing on stories collected during more than eighteen months of fieldwork, I produce an ethnohistorical account of the interrelated processes of formal tenure change and informalization through which neopatrimonial governance of land was established at Enoosupukia. Focusing on the participation in and instrumental use of formal and informal institutions by the current inhabitants of the area, I argue that clients in neopatrimonial political systems are neither mere pawns nor passive victims, but rather active, even if often marginal, participants. Applying this framework to explaining the genesis of violent conflict at Enoosupukia, I show that violence was not produced through top-down incitement, but rather through a convergence of patron and client interests in the context of a significant shift in the networks through which rights in land are claimed, challenged, and protected. The point is not to shift the blame for violence from the elite to the marginalized, but rather to show that manipulation of disorder is multidimensional. Further, while clients may benefit from neopatrimonial connection to instruments of state power through elite patrons, they remain insecure and subject to disconnection. Thus the security of rights depends as much on maintenance of connection as reference to formal law. This paper shows that while neopatrimonial governance may “work,” it is fragile.
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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 | 0.019 | 0.015 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".