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Record W2970504488 · doi:10.1002/sea2.12161

(Re)fashioning Philippine street foods and vending

2019· article· en· W2970504488 on OpenAlexaff
B. Lynne Milgram

Bibliographic record

VenueEconomic Anthropology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsLivelihoodPoliticsGovernment (linguistics)Consumption (sociology)LegitimacyInformal sectorBusinessProvisioningSustainabilityWork (physics)TasteEconomic growthPolitical scienceSociologyEconomicsLawEngineeringGeography

Abstract

fetched live from OpenAlex

A hallmark of many Global South city streets is ambulant vendors' daily trade in prepared and fresh foods. Yet governments often restrict such informal and sometimes illegal enterprises, privileging instead privatized and sanitized streetscapes—policies that disrupt urbanites' livelihoods and their consumption options. Engaging these issues, this article analyzes how street food vendors in Baguio, northern Philippines, mitigate the constraints of government street vending bans to establish viable and alternative food provisioning enterprises. I explore how vendors' location‐responsive political, social, and economic practices interweave with new street market design and consumption patterns to yield a distinctive taste of place while underpinning livelihood sustainability. Exercising “street politics,” some banned vendors joined the established Harrison Road Night Market, while others collectively established distinctive storefront eateries. That city officials enabled the legitimacy of formerly illegal and informal street vendors by incorporating their enterprises into these registered commercial venues evidences officials' complicity in formalizing informality when this policy is to their advantage. I suggest that through their politics‐on‐the‐edge, Baguio's relocated street food vendors emerge as effective visible actors in public arenas that have largely excluded their voices in where, and the conditions within which, they work.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.022
GPT teacher head0.332
Teacher spread0.310 · 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.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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