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Record W1604893227 · doi:10.1111/sjtg.12114

Itinerant livelihoods: Street vending‐scapes and the politics of mobility in upland socialist<scp>V</scp>ietnam

2015· article· en· W1604893227 on OpenAlexaff
Sarah Turner, Natalie Oswin

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsLivelihoodPoliticsNegotiationEthnic groupCONTESTState (computer science)Political scienceBusinessEconomic growthGeographyAgricultureEconomics

Abstract

fetched live from OpenAlex

This paper explores the politics of mobility for a group of rural inhabitants attempting to diversify their livelihoods in an especially prescribed environment, namely ethnic minority street vendors living and working in upland socialist V ietnam. These H mong, Y ao and G iáy individuals face a political environment where access and trade rights shift on a near‐daily basis because of the impulses of state officials, and where ethnicity is central to determining who gets to be mobile and how. We analyse three groups of itinerant vendors—those vending on the streets of an upland tourist town, the mobile minority wholesalers who supply them and other traders, and vendors who trek with Western tourists—to reveal the nature of this trade environment, while also highlighting the ways in which ethnic minority vendors negotiate, work around and contest vending restrictions in numerous innovative ways. We find that this focus on the micro‐geographies and everyday politics of mobility is essential to understanding how rural G lobal S outh livelihoods are fashioned and diversified, in this case revealing specific relationships and negotiations regarding resource access, ethnicity, state authority and livelihood strategies.

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)0.002
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 score0.409
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.020
GPT teacher head0.277
Teacher spread0.257 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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