Big Affect: The Ephemeral Archive of Second-Wave Feminist Video Collectives in Canada
Bibliographic record
Abstract
From 1972 to the early 1990s, Canadian feminist media collectives created dozens of social-issue documentaries and television series, producing an ephemeral archive of a vibrant era of political and social change. This article discusses the loss and/or deterioration of the material object of research, and it attempts, instead, to account for affect. In the absence of a complete audiovisual record, the passionate sites of embodied feeling experienced, remembered, and misremembered by the subjects of this history (including the author) become a way to reinscribe this history. Via interviews with collective members, screenings of archival works, and autoethnographic and archival research, the author examines the sites of feeling that accompanied the collective production of media works, as well as changes in public policy and the rise of neoliberal regulation that have impacted feminist organizing in Canada. The author argues that the lack of primary and secondary records of these collectives represents a significant gap in historical memory on several levels, signaling the forgetting of a moment when technology, public broadcasting, and feminist activism merged. As both participant and researcher, the author narrativizes this history in a way that moves beyond the absence or deterioration of a visual artifact, contending instead with ghosts, feelings, traces of memory and videotape, losses and gains, as well as with the productive dialogue and tension that occurs between historical forms of media activism and current digital platforms for feminist activism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.034 | 0.014 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".