Bibliographic record
Abstract
Chronique d’un Été [Chronicle of a Summer] is a documentary film studying young working people in Paris, made by visual anthropologist Jean Rouch, sociologist Edgar Morin, as well as Québécois cinematographer Michel Brault. The film is important for its early and concise expression of cinéma vérité aesthetics. For Chronique d’un Été, Rouch, together with engineer André Coutant, prototyped the first lightweight sync-sound 16mm camera operated in France. The film begins with Morin asking several people: ‘Are you happy?’ The question leads to political discussions ranging from colonialism, racism, and the Algerian War to the Holocaust. In one sequence demonstrating the film’s reflexivity, Marceline Loridan-Ivens, a Holocaust survivor and member of the French Resistance, walks alongside a tracking camera while dictating her grief-stricken memories into a hidden microphone. The film cuts to a separate long take of her walking forward while the camera accelerates away from its subject, her silhouette contracting while the volume of her speech remains static. Thus, Marceline’s voice becomes contrapuntal to her diminishing profile. This formal decision highlights the technically managed coordination between image and voice in documentary’s observational veracity. Does this signal that the documentary has intervened in reality? Or does it emphasise how the interview is aestheticised, constructing the spectator’s sense of truth? Such formal ambiguity defines cinéma vérité’s reflexivity.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.102 | 0.018 |
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".