Indictment: The Criminal Justice System on Trial
Bibliographic record
Abstract
#MeToo. Black Lives Matter. Decriminalize Drugs. No More Stolen Sisters. Stop Stranger Attacks. Do we need more cops or to defund police? Harm reduction or treatment? Tougher sentences or prison abolition? The debate about Canada’s criminal justice system has rarely been so polarized – or so in need of fresh ideas. Indictment brings the heartrending and captivating stories of survivors and offenders alike to the forefront to help us understand why the criminal justice system is facing such an existential crisis. It offers a new transformative justice vision – one that reviewers call “revolutionary” and “a beautiful vision for healthy communities that are safe for everyone”. Benjamin Perrin draws on his expertise as a lawyer, former top criminal justice advisor to the prime minister, and law clerk at the Supreme Court of Canada to investigate the criminal justice system itself. Indictment critiques the system from a trauma-informed perspective, examining its treatment of victims of crime, Indigenous people and Black Canadians, people with substance use and mental health disorders, and people experiencing homelessness, poverty, and unemployment. Perrin also shares insights from others on the frontlines, including prosecutors and defence lawyers, police chiefs, Indigenous leaders, victim support workers, corrections officers, public health experts, gang outreach workers, prisoner and victims’ rights advocates, criminologists, psychologists, and leading trauma experts. Bringing forward the voices of marginalized people, along with their stories of survival and resilience, Indictment shows that a better way is possible. [From Books]
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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.215 | 0.053 |
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".