Making home alive again after war: Acoli <i>Kaka</i> ’s Indigenous land sovereignties in Northern Uganda
Bibliographic record
Abstract
Abstract After the war between the Ugandan government and the Lord's Resistance Army (1986‐2006), 90 per cent of the displaced rural population in Northern Uganda returned to small‐scale farming on their ancestral lands and their systems of communal land stewardship. At the time, there was much debate about transitional justice interventions to address war's violence, but in that same period over 85 per cent of Acoli chiefdoms saw affiliated clans, or kin‐based political communities ( kaka ), negotiate to write down their Indigenous governance constitutions for the first time. Acoli Kaka ’s return to their ancestral lands and small‐scale farming, and subsequent engagements with tekwaro – Indigenous knowledge – through constitution writing, served to strengthen Indigenous governance and law after their weakening in contexts of war and displacement. It is argued here that these engagements and negotiations rooted in the land, regardless of their outcomes, served to orient relationships away from the fragmenting, unprecedented, forced Acoli‐on‐Acoli violence experienced during the war. A resurgence of Acoli Kaka ’s Indigenous law and governance rooted in communal land stewardship is linked to relational repair and supports calls for transitional justice processes to nurture and respect Indigenous land rights. These ethnographic arguments also lend support to kaka ’s ongoing efforts towards clan unity ( ribbe kaka ) and to secure communal land sovereignties.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".