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La Vía Campesina and its Global Campaign for Agrarian Reform

2008· article· en· W2122361773 on OpenAlex

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.

Bibliographic record

VenueJournal of Agrarian Change · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsIdeologyFraming (construction)Land reformExternalizationPolitical scienceAgrarian societyAgrarian reformPolitical economySociologyPoliticsLawAgricultureGeography

Abstract

fetched live from OpenAlex

Vía Campesina's ‘Global Campaign for Agrarian Reform’ (GCAR) has made a significant impact (inter)nationally in reshaping the terms of the land reform debates. However, its impact on other land policy dynamics has been marginal. Meanwhile, the campaign inadvertently exposed latent class‐based and ideological distinctions within the transnational network. This essay explains how the GCAR emerged, and has been able to influence the broader global land reform debates, but has not been able (so far) to significantly impact other major dimensions of the land policy debates. It argues that if GCAR is to retain relevance, it must deepen and broaden its current position on land to go beyond the parameters of conventional land reform. Moreover, it must also find ways to better integrate ‘global issue framing from above’ with ‘local/national campaigns from below’ if it is to strengthen its process of ‘issue/campaign externalization/transnationalization’. Doing this may require the network to rethink some of its well‐established organizational practices and ideological perspectives.

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 score0.753
Threshold uncertainty score0.254

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 head0.061
GPT teacher head0.237
Teacher spread0.175 · 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