Bibliographic record
Abstract
In the twentieth century, the Black Brazilian filmmakers who managed to accumulate a substantial body of work were few and far between, with a striking number of Black directors succeeding in making only one or a handful of films. Juliano Gomes examines how this landscape has changed in recent years, prompted by a new generation of film school graduates and reflected in landmark events such as the “Soul in the Eye” program at the International Film Festival Rotterdam in 2018, in which at least a quarter of the program’s films were made by students. His article focuses on two films representative of these changes: Ilha (2018), whose codirectors Ary Rosa and Glenda Nicácio met in the cinema course at the Federal University of Recôncavo da Bahia, and Travessia (2017), an award-winning student film by Safira Moreira.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.034 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".