Brakhage’s Tarkovsky and Tarkovsky’s Brakhage: Collectivity, Subjectivity, and the Dream of Cinema
Bibliographic record
Abstract
Malgré leurs différences évidentes, les films de Stan Brakhage et Andrei Tarkovsky présentent d’importantes similitudes tant formelles que thématiques. Notre article tire son argument de l’hommage que Brakhage rendait à Tarkovsky au Festival du film de Telluride en 1983, dans lequel il affirmait que le grand artiste de cinéma doit raconter les histoires de sa tribu, tout en demeurant personnel et en travai llant un matériau onirique. Notre hypothèse, selon laquelle ces cinéastes ont plus en commun que les critiques ne l’ont généralement reconnu, s’inspire aussi de la suggestion de J. Hoberman que Brakhage et Tarkovsky sont tous deux des surréalistes qui réinventent le langage cinématographique, des shamans nationaux à tendances religieuses et solipsistes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".