MAI Feminism & Visual Culture: Focus Issue Nine: Photography & Resistance
Bibliographic record
Abstract
Focussed on photography as a medium employed to counter patriarchal powers, uncover abuse, or document social resistance, our selection of articles celebrates the courage of female and non-binary people from around the world. We invite you to engage with them as, among many other forms of abuse and marginalisation, they oppose traditions, corruption, unfair treatment, or violence across all sections of their societies. First conceived by our brilliant guest editor Kylie Thomas from the NIOD Institute for War, Holocaust and Genocide Studies in Amsterdam, this issue documents how photography links with political, artistic, and personal moments of resistance on a larger or smaller scale. It took us over a year to commission, peer review and edit this issue with Kylie and her energetic collaborator, Brian Müller, a South African-born scholar based in Canada. Their drive to reach out to academics, artists and journalists helped start and develop this project, which was supported by a European Commission grant.* We hope that the writing and images you encounter in this issue will move, inspire, and above all, serve to remind you that resistance is always necessary and appropriate.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".