Documenting Urban Fictions in Contemporary Argentine Film: Notes on Pablo Trapero’s El bonaerense
Bibliographic record
Abstract
Buenos Aires holds a privileged place in contemporary Argentine film. Its protagonists roam the city streets under the sign of discovery or survival, evoking the capital’s monumental past and the smooth spaces of a new global presence. These cityscapes are constitutive of narrative meaning, chronotopes that open sites where fortunes change and paths intersect, making accessible a city whose recent transformations have been sudden and remain indecipherable. The characters decode the city as they move across it, interpreting its signs as they search or wander, translating the urban landscape that conditions their possible movements and encounters. Films as different as Pablo Trapero’s El bonaerense (2002), Alejandro Agresti’s Buenos Aires viceversa (1996) and Daniel Burak’s Bar “El Chino” (2003) open historic and affective trajectories through urban space, attempting to figure out the city, to figure the city, to find a figure that will make Buenos Aires legible after the multiple physical and civic changes arising with neo-liberalism. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".