There Is No Immersion: Critical Intervention through Hypermediacy in Metagames
Bibliographic record
Abstract
In 2020, Draw Me a Pixel released There Is No Game, a game that playfully engages with the concept of the metagame and its varied meanings to examine the relationship between developers, games, and their audiences. The game has much in common with other metagames released during the boom and bust cycle of the indie game market in terms of its themes and playful attitude toward its players. Like many of these games, it features an antagonistic narrator, who, upon launching the game, announces that there is no game. The concept of a game resistant to play has become a recurring theme in many metagames that critique industry pressures, trends, and players’ playful resistance to designed experiences. This article examines There Is No Game’s use of hypermediacy (as a feature of both its narrative and design) to deliver its critique of the industry, while offering insight into its own development. More than simply breaking the fourth-wall, hypermediacy becomes the instigator for critical reflection and is used to highlight the challenges faced by indie developers and the material conditions in which games are made. Yet, unlike its predecessors that share this critique, There Is No Game offers an optimistic perspective on the future of the industry.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.050 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.006 |
| 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".