'Subbed-Titles': Hollywood, the Art House Market and the Best Foreign Language Film Category at the Oscars
Bibliographic record
Abstract
This thesis provides a history of the Best Foreign Language Film category at the Oscars between 1926 and 2013. It examines the category through an industrial approach, historicizing the category’s symbiotic relationship with the Hollywood studios and examining how its financial, political and cultural parameters have been affected by changes within Hollywood studio corporate structure and the Hollywood studios’ practice of importing foreign-language films from Europe and around the world. Documenting this practice allows for the category to be structured in three sections: the period of European Art Cinema, the period of European commercial cinema, and the current period, which focuses on commercialized films that can be distributed worldwide. This study will ultimately suggest that the category acts as a prism that can be used to understand the industrial conditions and contexts of various forms of art and niche cinema at a global level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".