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Record W3215239510 · doi:10.1080/19320248.2021.2002747

“Fronts for Drugs, Money Laundering, and Other Stuff”: Convenience Stores in the Retail Food Environment

2021· article· en· W3215239510 on OpenAlex
Meghan Lynch, Catherine L. Mah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Hunger & Environmental Nutrition · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsDalhousie UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsBusinessContext (archaeology)MarketingSociocultural evolutionAdvertisingRetail salesSociologyGeography

Abstract

fetched live from OpenAlex

There have been calls for more research to investigate the sociocultural context of retail food environments. This paper examines how a segment of Ottawa, Ontario, Canada, residents described convenience stores (CS) in their local retail food environments. 84 social media discussions from Ottawa residents pertaining to their local retail food outlets were qualitatively analyzed, and three themes were formulated: 1) CS are interchangeable, 2) CS are not ‘real stores,’ and 3) CS are dangerous retail food outlets. We argue that these social constructions of CS have implications for healthy food environments and offer suggestions for future research.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.353

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 studies0.0000.000
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 head0.030
GPT teacher head0.255
Teacher spread0.225 · 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