Cine de lo real desde Barcelona: espacio, sonido, sugerencia
Bibliographic record
Abstract
This paper analyzes how space and sound are used by several documentary filmmakers in some of their late works. Although coming from different places, Barcelona is the city where, as many others in the last ten-twelve years, they have found proper environment and conditions for a creative, innovative cinema. A cinema with no boundaries between fiction and non fiction. All of these films tend towards a fragmented narrative and editing style which leaves empty spaces to suggestion. Many of these films, as well, use sound – voice, music, even silence – to add new meanings to images, in a surprising, disturbing or metaphorical way. Films by Jose Luis Guerin, Ricardo Iscar, Mercedes Alvarez, Joaquim Jorda, Ariadna Pujol, Isaki Lacuesta or Lupe Perez, all of them, as well, related to Master de Documental de Creacion in Pompeu Fabra University.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".