The Agony of Injustice: The Adversarial Trial, Wrongful Convictions and the Agon of Law
Bibliographic record
Abstract
This study examines the relationship between the adversarial legal system and wrongful convictions. Understanding the shortcomings of legal procedure as a contest, (especially in cases involving marginalized defendants), can be illuminated through a critical agonal analysis that reveals power imbalances and rule breaking. The paper addresses the trial of William Mullins-Johnson, a Canadian aboriginal man who spent 12 years incarcerated for a crime that never took place. The court is examined as an agonal space of contestation where victory in the adversarial trial is equated with factual, actionable truth. The analysis invokes the critical theory of agonism prefigured in Foucault’s under-explored theory of power as a ‘clash between forces.’ Although the adversarial system is premised on the value of fair play, the winner-loser structure can invite rule-breaking and violations of due-process to the gross disadvantage of the accused thereby reproducing forms of systemic discrimination and horrific miscarriages of justice. The aim of the study is not to provide a full synopsis of the Mullins-Johnson case but to suggest that agonistic theory can make critical contributions to understanding of the relation between adversarial legal contests and wrongful convictions.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".