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Record W4387227246 · doi:10.2307/jj.7249516

Video Game Characters and Transmedia Storytelling

2023· book· en· W4387227246 on OpenAlexfundno aff
Joleen Blom

Bibliographic record

VenueAmsterdam University Press eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
FundersEuropean CommissionUniversity of TorontoJohns Hopkins UniversityUniversity of MinnesotaWayne State University
KeywordsStorytellingVideo gameMultimediaVideo game designGame designArtVisual artsMedia studiesComputer scienceSociologyLiteratureNarrative

Abstract

fetched live from OpenAlex

Characters are a vital aspect of today’s transmedia practices. Combining theories on fictional persons from Japanese and Euro-American practices, this book discusses video game characters embedded in our popular media culture in which they are constantly produced and re-imagined. 
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\nThis book introduces the dynamic game character, a type of game character with a development structure that consists of multiple outcomes in a game. Through their actions and choices, players can influence these game characters’ identities and affect their possible destinies. 
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\nGames subvert the idea that fictional persons must maintain a coherent identity. This book shows that dynamic game characters challenge strategies of top-down control through close readings of the Mass Effect series, Persona 5, Hades, Animal Crossing: New Horizons and more. It is directed to all scholars interested in the topics of transmedia storytelling, video games, characters, and Japanese narratology.

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 categoriesMeta-epidemiology (narrow)
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 score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.231
Teacher spread0.203 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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