Becoming Gamesworkers: Diversity, Higher Education, and the Future of the Game Industry
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
Higher education qualifications and the training of talent have become increasingly important in game industry and policy discourse in the United Kingdom. This heightened rhetoric and dedicated pots of funding referencing the significance of the games talent pipeline may represent the opportunity to cultivate greater inclusion in the workforce, which continues to be largely homogenous in terms of gender and race. Drawing on qualitative research with stakeholders in five case study institutions, this article highlights the ways in which the production of gamesworker subjectivity by institutions, instructors, and students hinders this possibility. Transparency about the exploitative working conditions and exclusionary norms of the game industry instead becomes the grounds for aggressive and conservative performances of labor bravado, foreclosing collective action, moral arguments about addressing inequalities, and creativity. The article closes by addressing the tension between team-based collaboration and competitive individualism as a site of potential intervention.
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 | 0.000 |
| 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) | 0.003 | 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