Audible Efforts: Gender and Battle Cries in Classic Arcade Fighting Games
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
Video games are demanding work indeed. So demanding that our screen heroes and heroines are constantly making sounds of strife, struggle, or victory while conducting surrogate labor for us running, fighting, saving worlds. These sounds also represent the very real demanding labor of voice actors, whose burnout and vocal strain have recently come to the fore in terms of the games industries’ labor standards (Cazden, 2017). But do heroes and she-roes sound the same? What are the demands—virtual, physical, and emotional—of maintaining sexist sonic tropes in popular media; demands that are required of the industry, the game program, and the player alike? Based on participatory observations of gameplay (i.e., the research team engaging with the material by playing the games we study), close reading of gendered sonic presence, and a historical content analysis of three iconic arcade fighting games, this article reports on a notable trend: As games self-purportedly and in the eyes of the wider community improve the visual representation of female playable leads important aspects of the vocal representation of women has not only lagged behind but become more exaggeratedly gendered with higher-fidelity bigger-budget game productions. In essence, femininity continues to be a disempowering design pattern in ways far more nuanced than sexualization alone. This media ecology implicates not only the history of best practices for the games industry itself, but also the culture of professional voice acting, and the role of games as trendsetters for industry conventions of media representation. Listening to battle cries is discussed here as a politics of embodiment and a form of emotionally demanding game labor that simultaneously affects the flow and immersion of playing, and carries over toxic attitudes about femininity outside the game context.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it