Green Cultural Criminology: Foundations, Variations and New Frames
Bibliographic record
Abstract
Abstract Green cultural criminology (GCC) is a hybridized, interdisciplinary approach, drawing upon general propositions associated with green criminology and cultural criminology. Whereas green criminology is concerned with crimes and harms affecting the natural environment and the planet, including their associated impacts on human and nonhuman life, cultural criminology is focused on the ways and means by which crime and crime control are socially constructed, enforced, represented, and resisted. The directions of GCC are wide-ranging and can be expressed as forms of inquiry about (a) media and popular cultural representations of environmental harms, crimes, and disasters, including how difference, deviance, and resistance are constructed in regard to environments and spaces; (b) the dynamics and constructions of consumption, especially with respect to the commodification of nature; and (c) the contestation of space, transgression, and resistance in relation to environmental harms. Over time, variations in GCC have emerged to explore how the cultural production of meanings—namely meanings associated with environment, human, and nonhuman species along with the connections and linkages between them—structures and informs the various ways that we conceive and make sense of, think and feel about, as well as act toward, interact with, and make decisions regarding the environment. To enhance existing ways of thinking about GCC in a post-pandemic world, four additional “cultural frames” are suggested for investigation and analysis: ekphrasis, elite consumption, commodification of nature, and Black Sky Thinking.
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 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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.010 | 0.147 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".