To Archive Ephemera: The Importance of Atom Egoyan’s Collection at the TIFF Archives
Bibliographic record
Abstract
The advantage of a multi-faceted institution like the Toronto International Film Festival (TIFF) is its capacity for connecting different aspects of the film industry to one another. For example, TIFF’s archive houses a large quantity of ephemeral material that correlates to its databases; this binds collections together through metadata. The Atom Egoyan collection is particularly robust; all that stems from the wealth of information can be extracted from the paper ephemera that were donated in 1999. I use this opportunity to detail the general indispensability of ephemera when it comes to treating films as legacy objects and not just forms of entertainment, and by carefully examining and cataloguing the Egoyan collection, in particular. I created a digital catalogue that ties together item level titles, descriptions, dates, physical locations, and other forms of identification; this in turn builds upon the previous finding aid by strengthening the information taken from it.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".