Patriarchy in play: Video games as gendered media ecologies
Bibliographic record
Abstract
Videogames are a dominant cultural, economic and creative medium in the twenty-first century, whose varied ecologies are increasingly recognized as particularly hostile environments to those identifying or identified as women. These ecologies include those encoded and enacted within the virtual environments of digital games, across the spectrum of those ecologies materially inhabited in games education, game cultures and, paradigmatically, the video game industry. In June 2020, top videogame maker Ubisoft saw high ranking employees resign from the company as accounts went public on Twitter and in mainstream media of sexual harassment, abuse and other misconduct at the company being covered up and ignored. But this is by no means the first public revelation of sexual harassment and discriminatory injustices directed at women who develop and play games: many will recall the vitriolic online hate movement #gamergate. Despite the familiarity of these tropes, we seem to ‘rediscover’ every few years or so that making and playing video games can present toxic environments for women. Drawing on feminist perspectives that understand how videogames have been a gendered, primarily masculine, domain, this article proposes that a topographical view, one specifically attuned to examining gender through a media ecology lens, can demonstrate how these successive re-enactments of ‘shock and awe’ operate in the service of, and are functionally integral to, the preservation of media ecologies exclusionary by design, legitimizing the repetition of their gendered hostilities. The intent is to move beyond naïve expressions of surprise and righteous indignation, to a grounded recognition and elucidation of the extents to which misogyny and harassment are and have been deeply structured into the gendered ecologies of video games.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".