Feminist storytelling in the museum : Uncovering pedagogies of critique, possibility, and agency
Bibliographic record
Abstract
How are feminists resisting and disruptive normative, often millennia old patriarchal storytelling practices in museums around the world? This article shares my findings of the work of feminists in public art and history and women’s and gender museums and the different stories they tell in the interests of gender justice and change. Visiting exhibitions and perusing websites, I found a plethora of innovative practices of herstorying, animating, reframing, recentering, rescripting, gender bending and revisualizing that offered both a language of critique and a language of possibility. I argue that as feminists shatter the complacency of entrenched masculine narratives they are curating a new consciousness, memory and sense of agency. As practices of feminist adult education museum storytelling aims to transform experiences of oppression into critical insights and place women and others oppressed by gender norms into more significant roles as historical and contemporary knowers and socio-cultural actors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".