Bibliographic record
Abstract
Canadian Brett Story's most recent film, The Prison in Twelve Landscapes (2016), explores the American prison system, as well as the traditional sense of “landscape,” in an unusual way: except for the film's final shot, a drive-by of Attica State Prison nestled in the countryside of west-central New York State, we see no prisoners and no prison buildings—and few spaces we could call landscapes. Story's panoramic film reveals the multitude of ways in which the prison system is hidden in plain sight throughout the United States. In Scott MacDonald's interview with Story, the filmmaker explains the film's unusual approach and structure—as well as the struggle involved in getting the film made. Story's modest budget is the ultimate irony of The Prison in Twelve Landscapes, given the fact that the American prison system is the world's most extensive, and no doubt most expensive, system of incarceration on the planet.
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 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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.059 | 0.030 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".