Bibliographic record
Abstract
This essay develops the concept of “chronic collage” through an analysis of two recent works of media reperformance: Tanya Tagaq’s Nanook of the North (2012–) and Guy Maddin and Galen and Evan Johnson’s The Green Fog (2017). Both are remixes commissioned as live performances by film festivals. Tagaq created a resurgent and resistant new soundtrack to Robert Flaherty’s 1922 ethnographic film Nanook of the North and Maddin sampled media works shot in San Francisco to assemble a remake of Alfred Hitchcock’s Vertigo (1958), with a live soundtrack by Kronos Quartet. Taking an ecosophical approach, this essay describes chronic collage as an anti-extractivist critical technique that plays on lived archives of moving image memory across sites of expropriation, exclusion, and contested history. A dynamic form, chronic collage names the attempt to animate the affective agency of temporal objects.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.076 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".