Marc Edge — Pacfic Press: The Unauthorized Story of Vancouver's Media Monopoly
Bibliographic record
Abstract
Reviews 185 experienced by audiences within that half world, a universe of light and dark" (1 73).Through his examination of many films dealing with constitutional, criminal, civil, and international law, Chase concludes that while they provide a legal narrative to the audience, it is "a different kind of narrative, a different impression of the legal system than conventional legal narrative, the language of lawyers and courts."The "visualization of legality" can be more or less true, but it is impossible to "argue that movies are simply a mirror held up to a system of blind justice, providing one more authorized account . .." (1 80).Whether or not a realistic image of the American legal system is a reasonable goal for filmmakers, the fact remains that their productions provide some of the most powerful, if not the most powerful images that inform the audience's view of the system.This begs an important question that Chase chooses not to address in much detail: Should commercial filmmakers be expected to portray the American legal system in its pure form, or when it comes to the law is there still room for fiction?Aside from the minor criticisms above, however, Chase's extensive and well-written analysis offers much of interest to serious scholars and movie-buffs alike.In particular, Movies on Trial presents a well-argued case for the study of the legal genre of film as an essential means of gauging how people understand the rules, regulations and procedures of the American legal system.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.009 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".