Bibliographic record
Abstract
Mentoring Artists for Women's Art (mawa) has always existed within two realms: that which is and that which we imagine.On the one hand, the focus of the organization has been extremely practical, in keeping with a lineage of prairie cooperative movements: What needs to be done and how do we achieve it together?At its inception in 1984, the women and men of mawa recognized that gender inequality in the visual arts was rampant, blatant, and normalized.And they knew this could be changed.Armed with little more than an ad hoc committee and an idea -mentorship -they created the framework for an alternative learning centre dedicated to equal opportunity for all people, recognizing that gender justice is central to this mission.Many of mawa's groundbreaking innovations, such as the year-long Foundation Mentorship Program (see Noni Brynjolson's contribution in this volume), were conceived of as tools for change: if we share skills and information, no one will be isolated, marginalized, sidelined, or forced to reinvent the wheel within the privileged and opaque art world.The problem was named: systemic sexism.mawa programming offered and continues to offer a solution.This is the spirit that led to the book in your hands.Shockingly, there has never been a book about the diversity of feminist visual art in Canada nor theoretical reflections on the breadth of Canadian feminist art practices.We need such a book!So mawa has worked to create one, to begin this conversation.The transformative artworks of many women and feminists, past and present, have not been adequately documented.The affects of these works, the conversations they have inspired, and the shifts they have created have been left untended, too often ignored or sidelined.Feminist art remains marginalized, despite the advances of the past thirty years.So it is telling that the task of beginning to redress these canonical omissions fell to mawa, a small artist-run centre in Winnipeg.We are neither a university
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.770 | 0.723 |
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".