Bibliographic record
Abstract
Introduction The subject of food is simultaneously ubiquitous androutine. Spanning roles of biological nourishment,cultural representations, technological innovations,religious proceedings, medical components, socialoccasions and personal tastes and pleasures, foodsurrounds and intertwines the myriad of humanexistences and ways of life. Yet individuals’experiences with food remain habitual, mundane,regular and perhaps increasingly void or withdrawn.The importance of food, in all its roles, cannot beunderstated. Food decisions and practicesfiguratively and literally invade the very being ofhumanity, having deliberate and unintentional globalimplications on every measure of public welfare,individual wellbeing and environmental health,impacting both human and non-human animals andenvironments in the present and the future. Thus, it is quite easy to justify concern for food andfood systems, especially when there are problemsranging from global agricultural land grabbing, tohorsemeat scandals and mad cow disease, toineffective corporate self-regulation of foodsafety, to the harmful transport conditions oflivestock, to the consequences of food patent laws,to the impact of contemporary food systems onclimate change and the over-responsibilisation ofthe rational and ethical consumer – to name just afew. These concerns extend across the processes offood production, processing, marketing,distribution, disposal and consumption, acrossdecisions about growing and harvesting, agriculturallabour, levels of food safety, effective labelling,the use of different and new technologies, theconsequences of food processes on peoples andenvironments, and questions of the role andregulation of the individuals, private corporationsand public governments involved in all of theseissues. The purpose of this chapter is to provide a perspectiveon the ways in which harmful practices with negativeconsequences are involved along the food chain,anywhere from agricultural inputs to individuals’digestive systems. More specifically, this chapterassesses the decisions, practices, organisations,omissions or other ways actors engage in society,which involve illegal, criminal, harmful, unjust,unethical or immoral food-related issues, andbroadly defines them as foodcrimes . This may include situations oflaw-making or law-breaking, suspect or ineffectiveenforcement or the lack thereof, harms resultingfrom insufficient or absent regulation, orphilosophical and pragmatic questions of corruption,deviance, justice and erroneousness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".