Bibliographic record
Abstract
This chapter treats computer game playing as an affective activity, largely guided by the audio-visual aesthetics of game content (of which, here, we concentrate on the role of sound) and the pleasure of gameplay. To understand the aesthetic impact of game sound on player experience, definitions of emotions are briefly discussed and framed in the game context. This leads to an introduction of empirical methods for assessing physiological and psychological effects of play, such as the affective impact of sonic player-game interaction. The psychological methodology presented is largely based on subjective interpretation of experience, while psychophysiological methodology is based on measurable bodily changes, such as context-dependent, physiological experience. As a means to illustrate both the potential and the difficulties inherent in such methodology we discuss the results of some experiments that investigate game sound and music effects and, finally, we close with a discussion of possible research directions based on a speculative assessment of the future of player-game interaction through affective sound.Request access from your librarian to read this chapter's full text.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".