A Feminist Utopian Perspective on the Practice and Promise of Making
Bibliographic record
Abstract
While makerspaces are often discussed in terms of a utopian vision of democratization and empowerment, many have shown how these narratives are problematic. There remains optimism for the future of makerspaces, but there is a gap in knowledge of how to articulate their promise and how to pursue it. We present a reflexive and critical reflection of our efforts as leaders of a university makerspace to articulate a vision, as well as our experience running a maker fashion show that aimed to address some specific critiques. We analyze interviews of participants from the fashion show using feminist utopianism as a lens to help us understand an alternate utopian narrative for making. Our contributions include insights about how a particular making context embodies feminist utopianism, insights about the applicability of feminist utopianism to makerspace research and visioning efforts, and a discussion about how our results can guide makerspace leaders and HCI researchers.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.073 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".