Bibliographic record
Abstract
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.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".