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Breaking the Fourth Wall? User-Generated Sonic Content in Virtual Worlds

2013· book· en· W2623471744 on OpenAlexaff
Karen Collins

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMetaverseContent (measure theory)Human–computer interactionComputer scienceMultimediaInternet privacyVirtual realityMathematics

Abstract

fetched live from OpenAlex

Abstract The fourth wall is a term borrowed from dramatic theory that considers the theatrical stage as having three walls (two sides and a rear) and an invisible fourth-wall boundary between the actors and audience. This chapter considers the experience of user-generated sonic content in virtual worlds in terms of the concept of the fourth wall, situating this content in regards to the dynamic between audience and virtual space. While much of the work on user-generated content in virtual worlds has focused on this relationship between developers and players, there are many interesting aspects of user-generated content that have been neglected, particularly when it comes to sound. The chapter argues that user-generated sound is in a unique position with regards to breaking the fourth wall, presenting an overview of user-generated content in virtual worlds, and exploring how user-generated content contributes to the social interactions that occur and to the breakdown of the fourth wall. The chapter then focuses on the types of auditory content that are generated and shared between players, situating the use of sound as a mediator between the virtual and the real world spaces.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.958
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.228
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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