Bibliographic record
Abstract
Proceeding from a theoretical perspective, this chapter examines the various relationships that exist between consumer culture and crime. The chapter starts by looking at criminology’s past, and a short review of some of the main theories/theorists that have actually trained attention on consumerism as a criminogenic phenomenon. This section also includes a critique of the supposed oppositional potential of consumerism that dominated the social sciences until relatively recently. Turning to the present, the chapter then introduces three distinct but complementary perspectives that offer a more useful and critical explanation of ‘the crime-consumerism nexus’. First, cultural criminology addresses the criminogenic impact of global capitalism at the level of cultural discourse and everyday transgression. Second, ultra-realist criminology identifies the damage caused by consumer capitalism, and more specifically how the dominance of neoliberal ideology shapes the deep-rooted desires and drives behind much identity-driven criminality. Finally, the deviant leisure perspective draws on both these positions to illustrate how dominant forms of commodified leisure drive a range of social, environmental, and individual harms. The relationship between crime and consumerism is not a simple one but, as this chapter argues, it is one that demands serious and critical criminological attention.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
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".