Bibliographic record
Abstract
Abstract Prolific indie filmmaker Guy Maddin and his young collaborators, Evan Johnson and Galen Johnson, discuss their burlesque of Hyena Road (2015), and their attempts to bring imagined lost films to life in The Forbidden Room (2015) and in Seances, a National Film Board of Canada website where a cinephile can see a film made specifically for them, created on the spot, and existing for only that one viewing. Recently, the three collaborators also created The Green Fog (2017), a remake of Vertigo, using only clips of other films and TV shows shot in the Bay Area; Accidence (2018), a digitally constructed film that feels like Rear Window gone mad; and dream films evoked by Fellini. Their methods of working as a collaborative team are discussed at some length.
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 | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.025 | 0.028 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.048 | 0.017 |
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".