Bibliographic record
Abstract
Abstract This article appears in the Oxford Handbook of New Audiovisual Aesthetics edited by John Richardson, Claudia Gorbman, and Carol Vernallis. This chapter explores concepts of interactivity as they relate to sound production in video games. A guiding assumption of the chapter is that interactivity is a definitive paper of new digital aesthetics in general and gaming in particular. And yet, the question of interactivity has not been addressed with sufficient stringency in scholarly research. At the heart of the chapter are these questions: What makes interactive sound different from noninteractive sound? Where does interacting with sound fit into our understanding of our experience of sound and music in media? How do we begin to approach interactive sound from a theoretical perspective? The implications of interactivity are examined, specifically the notion of sound as a feedback device and as a control mechanism. . In these ways the chapter works toward a more comprehensive understanding of sounds in new media contexts that addresses their particularity in interactive contexts rather than resting on previous assumptions about the primacy of sounds as narrative devices.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".