MétaCan
Menu
Back to cohort

Bridging Policy and Practice ; Advancing Justice in Community Land Use Planning in Kenya

2025· article· en· W7134960187 on OpenAlexaff
Mwenda Makathimo, Robert Kibugi

Bibliographic record

VenueAfrican Journal on Land Policy and Geospatial Sciences · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsStatutory lawLand tenureCustomary landCorporate governanceAutonomyLand lawLand-use planningIndigenousLand use

Abstract

fetched live from OpenAlex

Context and background Community land rights in Kenya have endured historical and contemporary pressures since the colonial period. The imposition of English statutory tenure systems alongside African customary tenure established a dualistic framework that entrenched inequities and weakened indigenous land governance structures. The marginalization of customary law and practices has resulted in tenure insecurity, fragmented governance, and inadequate community participation in land use planning. This scenario presents both a governance challenge and a manifestation of historical injustice. Goal and Objectives: This paper critically examines the implementation of land use planning frameworks in Kenya, focusing specifically on community land. The objectives are to assess the impact of fragmented statutory planning authority on the autonomy of community institutions, and to explore avenues through which robust, community-led land use planning can advance equity, sustainability, and reparative justice. Methodology: A qualitative approach is adopted, utilizing legal and policy analysis of Kenya’s Constitution, the Community Land Act (2016), the Physical and Land Use Planning Act (2019), and related institutional frameworks. The analytical framework is guided by the principles of equity, sustainability, and tenure security.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.312
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAfrican Journal on Land Policy and Geospatial SciencesSame topicLand Rights and ReformsFrench-language works237,207