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Record W2763709736 · doi:10.1111/joac.12224

Migration and agrarian transformation in Indigenous Mexico

2017· article· en· W2763709736 on OpenAlexaff
James P. Robson, Daniel Klooster, Holly Worthen, Jorge Hernández‐Díaz

Bibliographic record

VenueJournal of Agrarian Change · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousCollective actionAgrarian societyArgument (complex analysis)EthnographyRationalityPolitical economyCorporate governanceSociologyPeasantPolitical scienceDevelopment economicsGeographyAgricultureAnthropologyPoliticsLawEconomicsEcology

Abstract

fetched live from OpenAlex

Abstract Migration is of particular concern to Indigenous peoples and communities. It physically separates those who migrate from the land upon which collective processes of labour and ritual practice are often based, it affects congruence between individual and collective rationality (as migrants make the choice to maintain or relinquish community membership), and it robs communities of the adult residents who can be essential for projects of collective action. Using the concept of comunalidad , created by Indigenous intellectuals in Oaxaca, Mexico to analyse the importance of alternative practices surrounding land, labour, governance, and ritual found in the region, we show that while Indigenous villages are profoundly affected by different forms of migration, migration itself is not necessarily a “death knell” for Indigenous peasants. We argue that communities struggle—often successfully—to find ways to evolve and reconfigure themselves economically and politically, incorporating migration into the fabric of their daily lives and organizational structures. To make this argument, we draw on ethnographic research conducted with Indigenous Oaxacan transnational communities, both in the United States and Mexico.

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)0.001
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 score0.718
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.068
GPT teacher head0.341
Teacher spread0.273 · 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

Citations25
Published2017
Admission routes1
Has abstractyes

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