“Destroy She Said..” \n Gendered bodies in public spaces
Bibliographic record
Abstract
Analysing everyday’s practices, De Certeau suggests that the rhetoric of walking functions just as an ‘art of speaking’. In this line we can argue that the way women and men stay and move in social space is a cultural gendered language and that their body is a significant product (and producer) of spatial practices and their related power inequalities. Quoting the title of Marguerite Duras short-story ‘Detruire dit-elle..”, the paper will present and discuss the deconstructive art works of some contemporary women artists as provocative actions to denounce and ‘destroy’ a visual spatial culture reflecting and reproducing the social invisibility of women body. This is the case of Austrian artist Valie Export which literally performed in Wien new measures of the urban space with her body, or the case of American artist Barbara Kruger which denounced with her big urban posters the social ‘order not to move’ addressed to women. Inspired by foucauldian analysis on disciplined society, the bodily machines of Canadian artist Jana Sterbak suggest how the everyday power reproduces symbolical and physical borders in public space, while female bodies of American sculptor Kiki Smith, tracing the space with their internal bodily matter, are provocative marking figures. Finally Italian artist Monica Bonvicini with her videos and installations represents and criticizes the strong claustrophobic connection between architecture, gender and social power.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".