An Intersectional Feminist Critique of Cyberlibertarian’s Grip on the Construction of Online Freedom
Bibliographic record
Abstract
Abstract The impacts of online hate speech include emotional and embodied harms that have sometimes stunted careers, resulted in lost wages and missed job opportunities, and damaged relationships (both personal and professional). Despite the real-world negative impacts of digital hate speech, many resist regulations that would mitigate these harms. What is behind the anti-regulatory stance against preventative measures to reduce online hate speech? We argue that similar to the “there is no alternative” to neoliberalism argument, which demonizes regulation and pushes traditionalism, the gendered construction of cyberlibertarianism presents online freedom as the only game in town, at least when it comes to online hate. We adapt Horton’s three-part framework of neoliberal masculinities to stress the role of gender in constructing various understandings of cyberlibertarianism. Through an intersectional feminist critique of cyberlibertarianism rooted in cyberfeminism and a critical feminist cybersecurity construction of online freedom, this paper adds to feminist cybersecurity and cyberfeminism by demonstrating how such approaches can counter cyberlibertarianism.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.073 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".