Bibliographic record
Abstract
Abstract This paper reviews the scholarly literature that connects transnational crime and policing through a critical discussion of the terms used to describe them. It is argued that authorized discourses regarding transnational crime are selective and partial. Ultimately, this results in two sorts of failures in contemporary transnational policing. It is a positive failure insofar as the ramping up of policing power in response to a global crime panic has come at the expense of civil liberties and human rights. It is a negative failure insofar as the transnational policing capacity that has been developed is unable to respond to the very real criminological consequences that are part of the downside of globalization. The surveillant assemblage of the emerging global policing security complex is an awesome and unaccountable power legitimitated on the basis of specified folkdevils. However, and despite well‐publicized claims to success, due to its own internal organizational pathologies and institutional fragmentation, the policing security complex is capricious. The article concludes by arguing that critical the examination of the concepts that constitute transnational crime and policing is a crucial contribution to theories of global governance.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".