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Record W3092346294 · doi:10.4324/9781003035466-15

The manifestations of game characters in a media mix strategy

2020· book-chapter· en· W3092346294 on OpenAlexfundno aff
Joleen Blom

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
FundersEuropean CommissionUniversity of CambridgeUniversity of OxfordYork University
KeywordsComputer science

Abstract

fetched live from OpenAlex

Transmedia practices assume that characters are foremost elements of a diegetic world and that the coherence of their identity is analogous to human persons. This chapter diverges from these assumptions by moving beyond the Westernized discourse of transmedia storytelling. It looks instead at characters whose coherence of identity is discontinuous when they appear in a Japanese media mix strategy. Both transmedia practices from the West and from Japan face a similar challenge when characters appear in videogames, caused by the structural differences between games and media with narrative affinities. Therefore, this chapter explores the challenge videogames pose to contemporary transmedia practices when a media mix strategy attempts to converge games with various narrative media. Through a case study of the Japanese role-playing game Persona 5 (2016) and its peripheral narrative media, this chapter reveals that while characters in a media mix strategy do not have to have a fixed coherent identity—even when the player can affect the characters’ identities within the videogame—the media mix’ property owner still maintains a position of authority to determine which identity should be counted as normative and which as heresy.

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 score0.964
Threshold uncertainty score0.771

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 science0.0000.000
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 head0.041
GPT teacher head0.281
Teacher spread0.240 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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