Smoke Screens and Cinematic Representations of the MOVE Bombing
Bibliographic record
Abstract
Abstract Premiering in 2013, Jason Osder’s documentary film Let The Fire Burn chronicles the Philadelphia Police Department’s 1985 bombing of the Black revolutionary organization, MOVE. The bombing and subsequent fire – which the police commissioner let burn through 61 homes – resulted in the deaths of six adults and five children as well as the displacement of 250 people. Composed entirely of archival footage, Osder’s representation invokes a historicization and delimitation of an un-ended story about anti-Black state violence that, this essay argues, results in the obscuring of both MOVE’s continued struggle for freedom and the social conditions that make such actions possible. By thinking through collective memories of Black suffering and the ways in which they are mediated amidst a continued global assault on Black people, Hunter-Young explores what the temporal and spatial properties of smoke, and its relationship to fire, may signal about the sociocultural work of Osder’s film.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".