MétaCan
Menu
Back to cohort
Record W4242572781 · doi:10.22215/etd/2014-10594

Geographies of Power, Subjectivity and Belonging: Campesino Land Claims in Inzá, Cauca, Colombia

2014· dissertation· en· W4242572781 on OpenAlexaff
Sarah-Jane Hamilton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsMulticulturalismSubalternPoliticsState (computer science)Political sciencePolitical subjectivityCollective identitySubjectivityLand rightsPower (physics)Gender studiesIdentity (music)SovereigntySociologyPolitical economyLawEthnology

Abstract

fetched live from OpenAlex

This project investigates how collective rights to land are rooted in blood and soil, and with what repercussions. In 1991, Colombia adopted policies of multiculturalism to codify rights for collective political subjects. Struggling against acute dispossession, social movements are using multiculturalism's openings in a bid to claim land. I argue that multiculturalism in Colombia spatializes and ethnicizes rights possibilities, particularly rights to land. The state privileges land claims by ethnicized political identity groups able to demonstrate an autochthonous presence in specific, delimited territories. Drawing primarily on semi-structured interviews with leaders of the Campesino Association of Inzá, Tierradentro (ACIT), I explore how the state simultaneously forecloses land claims by much of the subaltern population, while re-legitimizing its authority through a seemingly progressive agenda of rights protection. I also consider how recognition based on autochthony risks naturalizing divisions between similarly marginalized groups, and complements the oppressions and exclusions fostered by neoliberal globalization.

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 score0.146
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207