The Affective Labor and Performance of Live Streaming on Twitch.tv
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
This article explores affective and immaterial labor on the leading live-streaming platform, Twitch.tv, which boasts over one hundred million regular viewers and two million regular broadcasters. This labor involves digitally mediated outward countenance, including being friendly to viewers, soliciting donations, building parasocial intimacy with spectators, and engaging audiences through humor. We offer an examination of streamers broadcasting as a “character,” which we situate within the context of play becoming work, the labor of performance and acting, and the economic compulsions that shape cultural labor on Twitch. We draw on hundred interviews with professional and aspiring-professional game broadcasters conducted in 2016 and 2017 at gaming events across the United Kingdom, the United States, Germany, and Poland, alongside ethnographic research. This inquiry into the dynamics of digital games and labor underscores the importance of studying live streaming as part of a wider critical investigation of contemporary digital work.
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 | 0.001 | 0.001 |
| 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