Changing Customary Land Tenure System in Tivland: Understanding the Drivers of Change
Bibliographic record
Abstract
This study aims at highlighting the factors driving change in the Tiv customary land tenure system. The study observes that although all societies have rules that regulate how land is owned, inherited and transferred, these rules continually undergo changes due to a myriad of factors. In Tivland, the study has identified the factors driving change in the customary land tenure system as demographic change, conflict and migration, socio-cultural factors and the commercialization of agriculture. Keywords: Custom; Land tenure; Tivland; drivers of change Resume: Cette etude vise a mettre en evidence les facteurs de changement dans le systeme foncier coutumier au Tivland . L'etude constate que, bien que toutes les societes ont des regles qui regissent la facon dont la terre est possedee, heritee et transferee, ces regles subissent sans cesse des modifications en raison d'une multitude de facteurs. Au Tivland, l'etude a identifie les facteurs de changement dans le regime foncier coutumier sont le changement demographique, les conflits et les migrations, les facteurs socioculturels et la commercialisation de l'agriculture.Mots-cles: coutume; regime foncier; Tivland; facteurs de changement
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".