Queering New Cinema History: Affective Methodologies for Comparative History
Bibliographic record
Abstract
New Cinema History has tended to focus on developing microhistories of the exhibition, distribution, and reception of theatrical Hollywood and other mainstream cinemas. While such scholarship has been essential for understanding how cinema operates as a sociocultural institution, its focus on the highly public forms of cinemagoing that often followed Hollywood film has left untouched the sometimes furtive and deliberately hidden cinemagoing practices and microhistories of queer audiences, curators, and exhibitors throughout the mid-to-late 20th century. This paper intervenes in this state of affairs and queers New Cinema History. I situate film festival studies and New Cinema History within the same methodological and theoretical terrain and argue that the exclusion of queer film festivals from New Cinema History is a result of both the field’s methodological preference for big data, as well as a structural heteronormativity underlying its methodologies. I further argue that by following affect, ephemera, and anecdotes, New Cinema History can better account for queer and other marginalised cinema practices.
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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 | 0.028 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".