Bibliographic record
Abstract
Two Bicycles examines all of the films, videos, and television works that Jean-Luc Godard and Anne-Marie Miéville, two of the most important postwar filmmakers, did together. Jean-Luc Godard and Anne-Marie Miéville worked across forms, across media, and across countries. This book, the first to be devoted specifically to the work they did together, examines the way they expanded the possibilities of cinema by using cutting-edge video equipment in a constant search for a new kind of filmmaking. Two Bicycles moves slowly across France and Switzerland, with detours in Quebec, Mozambique, and Palestine. Their amazingly varied body of work includes a twelve-hour television series, some experimental videos, an acclaimed feature film with Isabelle Huppert, a cigarette commercial, and much else. Overall the book shows the degree to which this work departs radically from the legacy of the French New Wave, and in many ways shows signs of having been formed by the distinct culture of Switzerland, to which Godard and Miéville returned in the 1970s to set up their “atelier,” Sonimage. Two Bicycles offers a chance to explore a body of work that is as unique and demanding as it is rich and revelatory. Godard and Miéville have worked together for four decades but have never seemed more relevant.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.135 | 0.044 |
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".