The Politics of Torture, Human Rights, and Oversight: The Canadian Experience with the UN's Optional Protocol to the Convention Against Torture (OPCAT)
Bibliographic record
Abstract
Torture has long been denounced by the international community; the need to protect citizens from abuse at the hands of the state is a principle enshrined in international law. One area where abuse is common is within the correctional system and as a result, there is a need for oversight in places of detention. The Optional Protocol to the UN’s Convention Against Torture (OPCAT) is an international human rights instrument that acts as a preventive measure to monitor all places of detention through regular visits. Supportive of the OPCAT since its adoption, Canada has considered signature/ratification since 2002 but has yet to commit. The purpose of this study is to identify factors that have led to a delay in Canada becoming State Party to the OPCAT despite adherence to the principles that this instrument embodies. A policy analysis framework was utilized to conduct stakeholder interviews and review government documents. The concept of agenda-setting received special attention and content analysis of media reports and a review of government legislative activity were conducted to provide insight into the prevalence of the issue on the public and political agendas. The author argues that while there are real challenges that policymakers must overcome, the absence of political leadership has resulted in stagnation in the decision-making process. As a result, the issue has disappeared from both the public and political agenda. In order for progress to be made, political will must be created and the impetus to act (‘re-setting the agenda’) must come from civil society in the absence of government engagement on this issue.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.086 | 0.051 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".