Alfred W McCoy. A Question of Torture: CIA Interrogation, fvni the Cold War to the War on Terror (American Empire Project) New York: Henry Holt and Company. 2006. Pp. 290. $15.00.
Bibliographic record
Abstract
Grieveson details some fascinating consequences of the Sims Act (one enterprising distributor attempted to project a Johnson fight film across the Canadian border to be rephotograped in the U.S., though his plan to cross state borders in this manner and thus evade the law were thwarted in court!), he rightly emphasizes its most important legacy to film censorship, in the articulation of the commerce theory of cinema.In his conclusion, Grieveson goes on to show how the Mutual Film Corporation v. Ohio case first centered on property rights, but switched gears to a freedom of speech emphasis as it percolated up through the court system to the Supreme Court.The 1915 decision, then, merely finalized a conceptualization of cinema that had already been internalized by the film industry in its efforts to avoid censorship, though it guaranteed the long-term institutionalization of that framework.The film industry would ultimately win First Amendment protection in 1952, but even after that it would continue churning out de-politicized drivel for the most part.Policing Cinema expands our understanding of how that drivel came to dominate American cinema, and how nativist and racist agendas informed the classical Hollywood regime.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.014 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".