Films by Jesse Nishihata: Curating an Online Film Exhibition from CFMDC Storage Films
Bibliographic record
Abstract
This thesis is an applied project where I inspect and catalogue films from the Canadian Filmmakers Distribution Centre (CFMDC) storage and curate an online film program. CFMDC has more than 300 films in storage that have been withdrawn from its circulation collection and not processed for decades. In one box of storage films, there are several reels of Jesse Nishihata’s films including films not in the CFMDC catalogue and film elements. This thesis looks at how film curation could be a catalyst for preservation. The first two chapters provide the literature review and introduction to Jesse Nishihata. The third chapter documents the work and research done to identify the films, their condition and copyright holders. The fourth chapter focuses on the details in organizing the online film exhibition including film selection processes, website building, digitization, captioning, and promotion. Finally, this thesis offers recommendations on how CFMDC could proceed with the films currently in storage.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".