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Record W4301478190 · doi:10.46692/9781447336020.013

Food crime in the context of cheap capitalism

2018· other· en· W4301478190 on OpenAlexaboutno aff
Joseph Yaw Asomah, Hong‐Ming Cheng

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsCapitalismContext (archaeology)BusinessPolitical scienceGeographyLawArchaeology

Abstract

fetched live from OpenAlex

Introduction The production and sale of unsafe food, which typifiesthe concept of cheap capitalism, has become a globalconcern due to the increasing integration andinterdependence of contemporary societies. Forinstance, the marketing of genetically modified (GM)food worldwide poses potential harm to consumers(Walters, 2006). Additionally, millions of peoplearound the world are exposed to food poisoning, with350,000 dying annually from it (Sifferlin, 2015). Ingeneral, the issue of unsafe food is not a newdevelopment. For example, during the IndustrialRevolution in the UK, dangerous additives, includinglead and mercury, were added to milk production(Philips and French, 2000). Adulteration cases inthe US, Canada and Australia led to the passage ofanti-adulteration laws in the late 19th and early20th centuries (Pilcher, 2006). The recent rise of cases involving unsafe food,however, demonstrate a historic and disturbingpattern of consumers’ daily vulnerability to therisk posed by dishonest food corporationssacrificing consumer safety and health for economicgain (Walters, 2006, 2007; Croall, 2009, 2012;Cheng, 2012; Picard, 2012; Young, 2012;Ghazi-Tehrani and Pontell, 2015; Leighton, 2016). Inthe US, for example, the Peanut Corporation ofAmerica (PCA) knowingly distributed Salmonella -contaminatedpeanuts to manufacturers and schools between 2008and 2009, which led to nine deaths, and about 11,000illnesses (Leighton, 2016; see also Chapter 11, thisvolume). Similarly, the Sanlu Group consciously soldits melamine-contaminated infant formula toconsumers, which caused the death of at least sixbabies, and over 300,000 illnesses (Ghazi-Tehraniand Pontell, 2015). These cases of unsafe food,combined with the discursive reframing ofhuman–nature relationships by cheap food (seeChapter 2, this volume), demonstrate the growingproblem of cheap capitalism in the food sectorglobally. Using secondary data sources, including the media,regulatory bodies, interest groups and scholarlyliterature, this chapter explores unsafe food withinthe conceptual framework of cheap capitalism. Byexamining the nature and scale of unsafe food, itfirst argues that cheap capitalism is rampant andposes a greater risk to public health locally andinternationally. Second, it argues that the state,industry and the processes of globalisationtypically constitute the dominant factors drivingcheap capitalism in the food sector. Third, itargues that unsafe food in the Canadian context canproperly be understood within the global context ofcheap capitalism.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.020
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0110.000

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 head0.040
GPT teacher head0.266
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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