“Situating and sustaining feminist action: lessons from digital games inclusivity organizing”
Bibliographic record
Abstract
Scholarship on feminist action has exploded in the context of networked publics, demonstrating how platforms can support the formation of movements and the amplification of critical discourse. And yet examination of feminist action beyond these digital infrastructures reveals how their affordances and constraints may lead to overemphasis on some features of action, potentially obscuring others that do not align with platform norms valuing visibility, virality, and self-expression. Our analysis of the functioning and impact of an intersectional community organization aimed at fostering inclusivity in video games provides a necessary complement to the emphasis on digital feminist activism within feminist media scholarship. After over a decade of operations, the organization invited a team of researchers to conduct a qualitative, action-oriented research project with participants and organizers of the organization to better understand its impact. This study of Pixelles Montréal reveals unique spatial, temporal, and affective characteristics that may be more sustainable, particularly in terms of the wellbeing of community members and organizers. In this paper we outline the community’s practices of intersectional feminist activism in games and argue for the importance of bringing non-digital practices in conversation with networked feminist activism.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".