Twitch spouse: Livestreaming and the legacy of spousal labour in the video game industry
Bibliographic record
Abstract
Precarious careers in the games industry have long relied on the unpaid and largely feminized support of spouses and family members. This paper addresses the role of spouses and other domestic cohabitants in the production of live game broadcasts on Twitch, Amazon’s world-leading platform in live video entertainment. I introduce the heuristic of the ‘Twitch Spouse’ to underscore the crucial role that domestic partners have played as invisible workers in the wider games industry, whose precarious conditions have been extended by the rise of at-home livestreaming. Drawing from ‘playful’ interviews and ethnographic observation with 12 Twitch creators located across the United States and Canada, I delineate three themes by which the partners of Twitch streamers vitally contribute to livestreaming: collaborative space production, the management of intimacy, and timekeeping. Herein, I show how a theorization of the ‘Twitch Spouse’ will build future pathways for recognizing the intertwined struggles of domestic and digital work within the precarious horizons of the game industry. This paper argues that Twitch streamers’ conceptualizations of intimate partners’ supportive labour reinforce domesticity and visibility as co-extended forces in the evolving relevance of digital labour to contemporary capitalism.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".