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Record W3202121689 · doi:10.1080/01436597.2021.1965870

Agrarian climate justice as a progressive alternative to climate security: Mali at the intersection of natural resource conflicts

2021· article· en· W3202121689 on OpenAlexfundno aff
Daniela Calmon, Chantal Jacovetti, Massa Koné

Bibliographic record

VenueThird World Quarterly · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersInternational Institute of Social Studies, Erasmus University RotterdamInternational Development Research CentreUnited Nations Development Programme
KeywordsAgrarian societyNatural resourceClimate justicePeasantVulnerability (computing)Political sciencePoliticsEconomic JusticeResource (disambiguation)Climate changeEnvironmental resource managementEconomic growthDevelopment economicsGeographyAgricultureEconomicsLawEcology

Abstract

fetched live from OpenAlex

Natural resource conflicts in Mali in the last decade represent an important case to visualise the interconnection between land and climate issues. The country has received significant international attention in recent years both due to the announcement of large-scale land deals and due to its perceived vulnerability to climate stress. At the same time, Malian peasant movements have formed important networks of resistance and have been leading the pilot implementation of village land commissions to recognise and manage community resources, based on a new Agricultural Land Law. This paper explores emerging trends in natural resource politics through the lens of interactions between land and climate policies and discourses. We analyse the growing use of the frame of ‘climate security’ to associate climate change, conflict and migration in relation to countries such as Mali, by looking into the possibilities that this frame could shift focus and blame towards conflicts between marginalised groups and further close space for bottom-up participation. As an alternative, we explore the relevance of a platform of agrarian climate justice and the possibilities and challenges of enacting some of its principles through the implementation of the village land commissions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.014
Scholarly communication0.0070.003
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.238
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations17
Published2021
Admission routes1
Has abstractyes

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