From Crunch to Grind: Adopting Servitization in Project-Based Creative Work
Bibliographic record
Abstract
The digital game industry has embraced servitization - a strategic orientation toward customer centricity in production-based firms - to deeply monetize digital games. Though some note the resource-intensive nature of delivering services and suggest inherent risks in its adoption, extant literature is uncritical. This article draws on labour process theory to critique the impact of servitization on workers at the point of production. We conducted in-depth interviews at a large North American game development studio. The results show the human cost of servitization, generally overshadowed by financial considerations. Specifically, we theorize that servitization increases the indeterminacy of labour and this must be compensated for if servitization is to realize its cost-benefit potential. The result is an intensification of labour through additional control imperatives which make workers accountable to consumers through deterministic success metrics, impact the creative process and direct creative outputs in real time.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".