Normative Pluralism and Socio-Environmental Vulnerability in Cameroon: A Literature Review of Urban Land Policy Issues and Challenges
Bibliographic record
Abstract
African cities are experiencing rapid, unregulated growth, characterized by high land pressure and growing demand for housing and urban infrastructure. New arrivals often settle in vulnerable areas (wetlands, hills, flood) where land is cheaper and unregulated by public authorities. This type of settlement is accompanied by numerous land conflicts, exacerbated by the coexistence of formal and customary land tenure systems, which struggle to harmonize. In this context, public land regulation policies often remain centralized and ill-adapted, revealing their limitations in ensuring equitable and sustainable management of urban land. Faced with this gap, our systematic study explores the socio-environmental dynamics of this normative pluralism in land governance within Cameroonian cities. Our findings highlight the tensions and opportunities of this complex coexistence, which vary significantly according to city size (small, medium, and large), the colonial heritage (Francophone and Anglophone), and the dominant legal framework (civil law and common law). The analysis highlights the need to take into account historical, linguistic, and politico-administrative roots, which profoundly influence local forms of the institutionalization of normative pluralism and the associated socio-environmental vulnerabilities. This normative plurality underlines the importance of a hybrid system of land governance capable of integrating local specificities while ensuring land security for all. Future research will include comparisons with other African countries in order to understand transferable mechanisms for better land governance.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".