Access to Information (ATI) as a Double-Edged Sword for Critical Policing Research
Bibliographic record
Abstract
In perhaps no other area of scholarship is access to information (ATI) legislation as contentious and the stakes so high as in policing and security research. Although ATI has become an important mechanism by which researchers have been able to analyse security and police practices, there remain significant legislative barriers preventing access. A decade after 9/11, the need for increased scrutiny of government agencies tasked with security and policing remains high, as is evident from the proliferation of public and private policing, the advance of a general societal risk aversion, and the now ubiquitous nature of state security and surveillance. In this article we offer first-hand accounts that highlight the institutional imbalances between police organizations and researchers, and consider the potential long-term effects of ATI in this area of scholarship. ATI legislation in Canada is increasingly becoming both a tool for researchers to penetrate policing organizations and also a weapon with which security institutions can stymie critical inquiry. The significant amount of Canadian ATI research that has stemmed from national security scholars shows the difficulties faced in this field when attempting to exercise the “right to know.” The strident lack of transparency within security and policing institutions tips the balance of access versus secrecy towards the latter, under the ever-present assumption that secrecy equals security. However, this area of research plays an important role in political discourse by fostering public dialogue and raising awareness of questionable and illegal security practices. As Larsen points out, we have seen ATI used recently to shed light on politicized security issues such as the Arar Inquiry, the campaign to repatriate Abousfian Abdelrazik, and, most recently, the Afghan detainee transfer scandal.
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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 | 0.047 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.016 | 0.181 |
| Scholarly communication | 0.038 | 0.044 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".