Bibliographic record
Abstract
"Canadian Criminal Law in Ten Cases explores the development of criminal justice in Canada through an in-depth examination of ten significant criminal cases. Martin L. Friedland draws on cases that went to the Supreme Court of Canada or the Privy Council, including well-known cases such as those of Louis Riel, Steven Truscott, Henry Morgentaler, and Jamie Gladue. The book addresses such issues as wrongful convictions, the enforcement of morality, Indigenous experiences with criminal law, bail and trial delay, and the impact of the 1982 Charter of Rights on the criminal justice system. Friedland describes in a masterful way the factual background of each case and the political, social, and economic conditions of the time. Each character--the accused, judges, and counsel--is described in detail, as are the relevant laws and procedures. Friedland includes recommendations on how the criminal justice system can be improved, such as by creating a new federal commission devoted solely to criminal justice and by the enactment by Parliament of enhanced codes of evidence and criminal law and procedure. Canadian Criminal Law in Ten Cases is an indispensable guide to understanding the criminal justice system for lawyers, students, and anyone interested in criminal law and the administration of criminal justice."--
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".