When the net works: queer feminist creative practice on social media
Bibliographic record
Abstract
In this thesis I demonstrate how patriarchy, capitalism and white supremacy are subverted in the work of queer feminist artists, contributing to a holistic vision of political engagement aligned with craft ethics and the principle of maintenance.Social media use is read through the lenses of enthusiasm and ambivalence, with a focus on how the neoliberal logic of corporate platforms is undermined by artists and users alike.Through an emphasis on labour, I foreground the question of whether and in what contexts Marxist tools of analysis are elastic enough to encompass other historically situated forms of oppression than those that focus solely on class, drawing from a body of work on Marxist feminist theory.I begin with a theoretical chapter that maps the contours of online engagement through social media by queer and feminist artists, focusing on the conditions of capture that render users into units of profit, and the principle of becoming, encompassing that which draws users to platforms to express themselves and build community.I then shift to the Parker Bright's intervention at the 2017 Whitney Biennial, in which protest and performance art coalesced in the disruption of the reproduction of an historic image of black suffering by a white artist.Finally, I turn towards the web-based project Queering the Map, demonstrating what enthusiasm can do to animate queer life online.The kind of labour that goes into instigating and maintaining discourses for racial and gender justice on social media is often elided; taken as natural or given.This obfuscation gets to the heart of the way in which forms of protest and community building are seen as defensive and inevitable rather than constructive and spontaneous. RésuméCette thèse démontre la façon par laquelle le patriarcat, le capitalisme, et la suprématie blanche sont subvertis par le travail des artistes féministes"queer" qui contribuent à une vision holistique
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.071 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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; 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".