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Record W2977491382 · doi:10.5539/jgg.v11n3p25

The Implications of Land Tenure Systems on Socio-Economic Development in Kumbo Central Sub-Division, North West Region of Cameroon

2019· article· en· W2977491382 on OpenAlexvenueno aff
Cordelia Givecheh Kometa, Richard N. Asongsaigha

Bibliographic record

VenueJournal of Geography and Geology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsLand tenureCustomary landEconomic growthGovernment (linguistics)Land lawStatutory lawPopulationSecurity of tenureGeographyResource (disambiguation)Stratified samplingLand useBusinessPolitical scienceEnvironmental planningEconomicsAgricultureSociologyLawCivil engineering

Abstract

fetched live from OpenAlex

This study explores the impact of land tenure systems on the socio-economic development of Kumbo Central Sub-Division. The incompatibility of the Statutory and Customary land tenure and land laws in Kumbo brings about conflict between the land laws and land users at large. Land tenure insecurity and lack of land certificates are the major reasons for the slow growth rate in the socio-economic development of Kumbo. This study seeks to assess the reasons for tenure insecurity and implications on the socio-economic development of Kumbo. Data necessary for the realization of this study were obtained through primary and secondary data collection techniques such as questionnaires, interviews, field observation, focus group discussions, snap shorts and the review of related documented materials. These techniques followed a stratified sampling on an age selective population that was liable to have access to land. The study revealed that land ownership and land use conflicts emanate from poor and incompatible land tenure systems in Kumbo. The study recommended that the problem of incompatibility between the two tenure systems can be resolved by harmonizing the two laws. Also, the Social Tenure Domain System was recommended to solve the problem of land tenure insecurity if well implemented by the Government of Cameroon. This model enhances land tenure security for all, especially the vulnerable groups. If all these recommendations are implemented effectively, socio-economic development in Kumbo will be greatly accelerated.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.013
Threshold uncertainty score0.085

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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