Person(s) of Interest and Missing Women: Legal Abandonment in the Downtown Eastside
Bibliographic record
Abstract
The criminal prosecution of Robert Pickton involved an eleven-month jury trial, two appeals to the British Columbia Court of Appeal, an appeal to the Supreme Court of Canada, and seventy-six reported judicial rulings. This article, through a combination of discursive and doctrinal analyses of these seventy-six decisions, examines what was (not) achieved by the Pickton trial. It discusses three areas: the judicial representation of the women Pickton was prosecuted for murdering; the implications of the jury’s verdict in the Pickton proceedings; and the impact of the Pickton trial on the families of the women he murdered. The article starts from the premise that it is correct to characterize these murders as a product of collective violence. Colonialism, political and legal infrastructure, and public discourse—and hegemonies based on race, class, and gender that these processes, institutions, and practices hold in place—produced a particular class of vulnerable women, the police who failed them, and Robert Pickton. The article concludes by suggesting that the outcomes of the Pickton prosecution both highlight the limitations of the criminal justice system and offer an analytical framework for examining other institutional responses (such as the Missing Women’s Inquiry) to the kind of collective violence that gave rise to the Pickton circumstance.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.046 | 0.029 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".