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Record W4200291939 · doi:10.1111/joac.12472

Land reform and peacebuilding in Côte d'Ivoire: Navigating the minefield

2021· article· en· W4200291939 on OpenAlex
Matthew I. Mitchell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Agrarian Change · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research Centre
KeywordsPeacebuildingPoliticsLand reformAgrarian reformPolitical scienceGovernment (linguistics)Civil societyPolitical economyPublic administrationDevelopment economicsEconomic growthSociologyLawEconomicsGeography

Abstract

fetched live from OpenAlex

Abstract This article explores the complex links between land reform and peacebuilding through a case study of Côte d'Ivoire. The country provides fertile ground for analysis given its torturous history of land conflict and civil war, its enduring debates surrounding land reform, and its ongoing efforts to consolidate peace. The article argues that while the failure to address the agrarian dimensions of the country's longstanding conflict undermines long‐term prospects of bridging deep political and societal divides, aggressive attempts to tackle the land question at the outset of the peacebuilding process may have threatened the fragile peace of the post‐conflict period. The analysis thus highlights the political risks involved in undertaking land reform during periods of precarious peacebuilding. In so doing, the article draws upon insights from over 70 interviews with local stakeholders and document analysis of key primary documents from the Ivorian government, the United Nations Security Council, and the World Bank.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.124

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 head0.036
GPT teacher head0.237
Teacher spread0.201 · 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