A Right to Know? Using Access to Information as Method in Critical Criminological Research
Bibliographic record
Abstract
Access to Information and Privacy (ATIP) requests are becoming an increasingly common method of qualitative inquiry, particularly for critical criminologists in Canada who face barriers in accessing Canadian prisons to conduct research. This article explores the politics of institutional gatekeeping and highlights the ongoing policing of critical criminological knowledge, necessitating the use of ATIP as a data collection method. Two case studies describe the strategies that the authors mobilized to acquire records from the Correctional Service of Canada (CSC) when their applications to conduct research inside prisons were denied. The authors argue that while access to information legislation is promoted as allowing for increased accountability and transparency of the government, real transparency is a public myth. This lack of transparency is linked to the ascendancy of administrative criminology in Canada, which ultimately devalues critical research and inhibits information flows in and out of carceral spaces.
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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 | 0.256 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.024 | 0.161 |
| Scholarly communication | 0.033 | 0.030 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".