PASSION, PIPELINES, AND PRECARITY: WORKING LIVES IN GAMES FROM THE PERSPECTIVE OF HIGHER EDUCATION
Bibliographic record
Abstract
For years, academics and journalists have proclaimed a crisis of gameswork, detailing the ‘destruction’ of the lives of those in this creative workforce, and wondering when the ‘breaking point’ of professional game design, premised on crunch, work limbo, and churn, would come. Still it was only at the March 2018 Game Developers Conference, typically a heavily corporatized event, that a large-scale discussion of unionization was staged, leading to the formation of Game Workers Unite. While collective organizing in games is going global, with branches forming from France to Australia to South Korea, these developments are outpaced by increasingly transnational dynamics of outsourcing and automation, threatening to devalue and even eliminate already highly-competitive jobs in ‘cool industries’ of ‘passionate’ workers. This paper considers these global contradictions and tensions through analysis of a group heavily implicated in visions of the future of gameswork- students in formal games education. While within game studies there has been sustained interest in the production of this form and labour relations therein, the shape and role of games higher education remains underexplored. The existing scholarship indicates that these formal sites of training tend to cultivate the still-largely young, male, and passionate fan-workforce on which games depend. Furthermore, these contexts are vital in the formation of future gamesworker identities that are conservative, uncritical, and risk-adverse, despite pervasive discourses of creativity and innovation linked to them. Vitally, however, the question of how these norms relate to shifting work realities has yet to be explored.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.051 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".