Emergent distribution strategies and feminist media practices: the case of <i>Groupe Intervention Vidéo</i> (GIV)
Bibliographic record
Abstract
Groupe Intervention Vidéo (GIV) is a Montreal-based distribution company “dedicated to the promotion of works made by women (in the most inclusive definition).” Founded in 1975, for almost five decades, GIV has supported a vast range of video works by and for women from Quebec and Canada, as well as from an international context. Over the years, GIV has promoted its catalogue to different communities through curated programs screened locally or at national and international festivals. More recently, this mandate has found a new venue and greater amplitude due to the use of two streaming platforms, Vimeo and VUCAVU. In this essay, I explain GIV’s recent discourse on the use of streaming platforms as reflective of the organization’s investment in video technology as a form of feminist intervention since the 1970s.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.033 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".