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Transnational Agrarian Movements Struggling for Land and Citizenship Rights

2009· article· en· W2134069353 on OpenAlexaff
Saturnino M. Borras, Jennifer C. Franco

Bibliographic record

VenueIDS Working Papers · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsCitizenshipCognitive reframingPolitical scienceTransnational governanceAgrarian societyCivil societyPublic administrationAgrarian reformPolitical economyEconomic growthSociologyLawGeographyEconomicsAgriculture

Abstract

fetched live from OpenAlex

Summary Rural citizens have increasingly begun to invoke perceived citizenship rights at transnational level, such that rural citizen engagements today have the potential to generate new meanings of global citizenship. La Vía Campesina has advocated for, created and occupied a new citizenship space that did not exist before at the global governance terrain – a public space distinct for poor peasants and small farmers from the global South and North. La Vía Campesina's transnational campaign in protest against neoliberal land policies is a good illustration of this in the sense that rural citizens of different countries collectively invoke their rights to define what land and land reform mean to them, struggle for their rights to have rights in reframing the terms of the global land policymaking, and demand accountability from international development institutions. It has been inherently linked with campaigns for land and citizenship rights. One of the outcomes of this initiative is that the public space created and occupied by various civil society groups got expanded. Such space has also been rendered much more complex, with the subsequent creation of various layers of sub‐spaces of interactions.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0070.004
Open science0.0000.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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 designQualitative
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

Citations37
Published2009
Admission routes1
Has abstractyes

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