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Record W2053304771 · doi:10.1002/sea2.12016

Unsettling Urban Marketplace Redevelopment in Baguio City, Philippines

2015· article· en· W2053304771 on OpenAlexaff
B. Lynne Milgram

Bibliographic record

VenueEconomic Anthropology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsOntario College of Art and Design
FundersChina Scholarship Council
KeywordsLivelihoodRedevelopmentPoliticsPublic spaceBusinessWork (physics)Political scienceLawGeographyEngineering

Abstract

fetched live from OpenAlex

Urban public marketplaces in Global South cities host a vibrant mix of retail and wholesale trade. Yet local‐to‐national governments increasingly promote sanitized and privatized urban spaces by privileging modern retail outlets (malls and supermarkets) and discouraging “traditional” livelihoods (street vending and market stalls). These political decisions dramatically disrupt the public market trade that has provisioned urbanites for decades. To address this issue, this article analyzes how retailers working in the renowned Baguio City Public Market, northern Philippines, sustain their livelihoods given that Baguio City's first phase of market redevelopment failed to meet their needs (e.g., insufficient store size and banning enterprises). Problematizing legal–illegal work and urban public space use, I argue that public marketers engage everyday and insurgent public space activism to protest their disenfranchisement. Although marketers generally have achieved selected demands, some have benefited more than others. Thus, I suggest that we consider not only marketers' resistance but also the uneven political landscape within which they work—the power differentials among and between marketers and the state. The extent to which variously positioned marketers can realize livelihood rights highlights the unpredictability of civic engagement and “extralegality” when competing ideologies clash over access to urban public space, legal–illegal practice, and appropriate urban provisioning .

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.998

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.364
Teacher spread0.295 · 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 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

Citations15
Published2015
Admission routes1
Has abstractyes

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