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Record W3008722167 · doi:10.18584/iipj.2019.10.5.8584

Production, Development, and Environmental Policies: Paradoxical Landscapes in Colonia Aborigen Chaco (Ex-Aboriginal Reserve of Napalpí, Argentina)

2020· article· en· W3008722167 on OpenAlexvenueno aff
Carlos Salamanca

Bibliographic record

VenueInternational Indigenous Policy Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Cultures and History
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousSettlement (finance)State (computer science)EthnographyConstitutionGeographyEthnologyPolitical scienceSociologyEnvironmental ethicsArchaeologyLawEcologyBusiness

Abstract

fetched live from OpenAlex

This article examines the experience of an Indigenous development plan carried out between 2005 and 2010 in Colonia Aborigen Chaco, an Indigenous settlement located in Chaco province, Argentina, originally established in 1911 as the Aboriginal Reserve of Napalpí. On the reserve, inhabitants were forced to settle down as the State appropriated their traditional territories. Here, I propose a critical analysis of this experience with ethnographic description pertaining to the long historical processes that inhabitants of Colonia Aborigen endured, which systematically subjected them to alimentary, educational, productive, and religious routines aimed at transforming them culturally. I intend to demonstrate that it is necessary to review a series of assumptions, which are quite prevalent in Indigenous policies, about what an Indigenous person, an Indigenous territory, and an Indigenous development are supposed to be. I emphatically assert that it is necessary to have a critical approach towards these historical processes of constitution in order to better understand the expectations Indigenous people have about their realities and development.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.011
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.318
Teacher spread0.298 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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