Using cultural criminology to think differently about war and terrorism
Bibliographic record
Abstract
In recent years, cultural criminology has established something of a foothold in Brazil (Ferrell, 2012;Ferrell and Hayward, 2013;Hayward and Young, 2015;de Carvalho, 2010;de Carvalho et al, 2011).But what exactly is 'cultural criminology'?Above all else, it is a theoretical, methodological, and interventionist approach to the study of crime and deviance that places criminality and its control squarely in the context of culture, i.e. it views crime and the agencies and institutions of crime control as cultural productsas creative constructs enmeshed in complex processes of meaning-making.Attentive to the realities of a deeply unequal world, cultural criminology strives to highlight how power affects the upwards and downwards construction of criminological phenomena: how rules are made, why they are broken, and the deeper implications of these processes.Because of its deliberately broad focus, the interests of cultural criminology are not easily summarized, but by way of a general introduction we can say that they include inter alia situated and symbolic meaning (e.g.Ferrell, 1996); existential and phenomenological aspects of offending space (e.g.Katz, 1988, Lyng, 1990); place and the (cultural) geography of crime (e.g.Hayward, 2004Hayward, , 2012)); subcultural and post-subcultural analysis (e.g.Ferrell and Sanders, 1995; Ilan, 2015); vicissitudes of power, resistance and social and state control (e.g.Presdee, 2000; Hayward and Schuienburg, 2014); the 'crime-consumerism nexus' (e.g.Hayward, 2003;Hayward and Smith, 2017); 'deviant leisure' and related forms of environmental harm (e.g.Brisman and South, 2014;Ferrell, 2013;Smith and Raymen, 2016); and the mediated construction of crime and punishment (including the commodification of violence and the marketing of transgression) (e.g.Rafter, 2000;Brown, 2009;Hayward and Presdee, 2010).Alongside these now well-established areas of engagement, the last decade or so has also seen cultural criminology develop a more sustained interest in the ongoing socio-economic transformations and fluctuations precipitated by neo-liberalism and associated modes of hypercapitalism.In part, this broader position has been a response to the criticism emanating from the radical left of the discipline that cultural criminology lacks ideological ballast and therefore is not political enough. 2 But equally this greater emphasis on the wider political consequences of crime and control is the consequence of a very deliberate attempt by cultural criminologists to develop a thoroughgoing 'cultural criminology of the state' (e.g.Burrows, 2013;Cunneen, 2010;Hamm, 2007;Klein, 2011;Linnemann et al., 2014;Morrison, 2006 Morrison, , 2010;; Wall and Linnemann, 2014a).Initially, this body of work focused largely on countering the state-centric discourse surrounding the various "wars" on drugs, gangs, and crime, and the mass incarceration machinery that follows in their wake (see e.g.Kraska, 1998;Ferrell, 2003; Wall and Linnemann, 2014b;Linnemann, 2016;Schept, 2016).More recently, however, it has also
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".