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Record W4390918054 · doi:10.1111/tran.12659

Making futures in Oaxaca: Remittances in the diverse economies of social reproduction

2024· article· en· W4390918054 on OpenAlexaff
Araby Smyth

Bibliographic record

VenueTransactions of the Institute of British Geographers · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsYork University
FundersPhilanthropic Educational OrganizationNational Science Foundation
KeywordsReproductionSocial reproductionIndigenousScholarshipFutures contractSociologyEthnographyProduction (economics)Scale (ratio)EconomyEconomicsPolitical economyEconomic geographyEconomic growthSocial scienceGeographyEcologyAnthropologyBiology

Abstract

fetched live from OpenAlex

Abstract In this article, I analyse intermingling economically productive and reproductive work at the global and local scale through the lens of how remittances are folded into the communal social relations of one Indigenous community in Oaxaca. Scholars have illustrated the many ways that social reproduction is reconfigured through transnational labour migration, and troubled the categorisation of economically productive and socially reproductive labour. Expanding on their work, I engage with scholarship about Indigenous communal governance in Guatemala and Mexico, particularly the theories of Gladys Tzul Tzul on reproduction, in order to present new insights into feminist geographical knowledge of diverse economies and social reproduction. Drawing on ethnographic methods, I present three empirical examples, which illustrate how the intermingling of economic production and reproduction of communal life make Indigenous futures. I argue that large‐scale reproductive activities, such as those deployed by the community, produce values beyond capitalist circuits of production and that it is how remittances are inserted into the local communal economies that render the money valuable for reproducing life and securing a future.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.294
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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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