Do-It-Together: Feminist Reconfigurations of Hacking in Montreal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technological practitioners and observers often depict hacking cultures as fast-evolving spaces for social, political, technological and cultural innovation. While interest in hackerspaces is growing in terms of technological innovation, limited attention has been paid to building inclusive collective real-world spaces for hacking. This dissertation addresses this lacuna in two ways: First, this study looks into the forms of inclusion and exclusion found in traditional hacking spaces, exploring in detail the invisible boundaries formed in and around such spaces. Second, this study foregrounds feminist hacker practices and the alternatives they offer to such limited traditional hacking spaces. It argues that traditional hackerspaces, while empowering a few, encourage segregation within the hacker movement and enforce unwritten norms that relegate a large number of hackers (female, queer, transgender among others) to the margins or even the outside. To this end, this thesis examines two case studies in the city of Montreal: Foulab, a traditional hackerspace, and Femhack, a feminist hacker collective. As a hacker, a feminist and a researcher, I chose to study these communities through an Ethnographic Action Research Methodology, a methodology which helped me to document, contextualize and analyze the local expressions of the hacker movement, while theorizing its real and potential approaches to space, community-building, and learning through technology. By using the advantage of my insider position, this research assesses the democratic limits and possibilities of hackerspaces in Montreal and beyond. It offers four takeaways: 1) The traditional hackerspace model reproduces patriarchal structures that create barriers for women and other minorities, due to an overemphasis on technology and individual achievement. 2) Feminist hackerspaces welcome participants and are actively inviting, not just welcoming in theory. Choosing to invite marginalized hackers in is more powerful than just “leaving the door open” for them. 3) Broadening the definition of hacking to include areas in which men are not already the default experts, creates a more just, diverse, and equitable hacker field of expertise, thus breaking hierarchies and power relationships in this technological field. 4) Feminist pedagogies stressing on collaborative learning and applying in the hacker practice open the barriers set in traditional hackerspaces, creating spaces respectful of participants’ differences and needs. In a nutshell, I suggest that the ideals and practices of the feminist hackerspace examined in this thesis could be the beginning of a movement from a DIY (do-it-yourself) toward a DIT (do-it-together) hacking culture focused on more connected local communities, encouraging sustained engagement and more inclusive participation in the hacker movement.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it