Bibliographic record
Abstract
As an early theorist of cyberfeminism – a discourse coalescing in the late 1980s and early 1990s around feminist reexaminations of information and communication technologies – Canadian artist Nancy Paterson’s practice took shape within and against the commercialization of the internet, a situation she addressed explicitly in her scholarly work in information policy studies toward the end of her life. This paper analyzes her 1990s networked installation Stock Market Skirt as shaped by Paterson’s understanding of the political commitments and possibilities of cyberfeminism, set against an archetypical image of the “cyberfemme”: seductive, uncanny, and doll-like, though technologically adept and adaptable. Stock Market Skirt links the movements of a motorized dress with real-time stock data mined from financial websites, critiquing feminism’s altered relationship to contemporary capitalism. The work manifests a feminized “flexible personality,” an image of neoliberalism’s decentralization of power from the state to the network, presenting it as the flip side of cyberfeminism’s attempt to liberate subjectivity from static conceptions of identity. In this way, Stock Market Skirt connects flows of capital with attributes of gender performance, prefiguring algorithmic, image-based reinforcement of contemporary gender ideals, effects of the tech industry’s efficiency in linking behavioral data to ad targeting.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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 teacher head, 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".