Intersectional Criminologies for the Contemporary Moment: Crucial Questions of Power, Praxis and Technologies of Control
Bibliographic record
Abstract
This article reflects on the growing acceptance of intersectional criminology alongside emergent challenges of the contemporary moment. In light of social changes, the article asks: What is important about intersectionality and its relationship to criminology? How might we sustain and nurture these crucial dimensions and connections? Exploring answers to these questions, we consider how to retain intersectional commitments in areas of increasing importance, such as ubiquitous surveillance and technologies of policing. In discussing how we might examine and unpack the workings of interlocking systems of oppression and their effects, this article addresses how intersectional criminologists might reflect more critically on their methodologies to ensure robust analysis and incorporate frameworks that better capture the technosocial entanglements emblematic of ongoing shifts in social control. After reviewing approaches for doing so, the article concludes with a reflection on implications for intersectional criminological praxis.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.016 | 0.213 |
| Scholarly communication | 0.030 | 0.036 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".