The Synchretic Network: Linking Music, Narrative, and Emotion in the Video Game Journey
Bibliographic record
Abstract
In the 2012 video game Journey, music is an important component of the playing experience. This study adopts an interdisciplinary approach, drawing on narratology, semiology, and film-sound theory to examine the relationship between music, narrative, and emotion in Journey. After first discussing video games’ interactivity in general, philosopher Dominic Lopes’ theory of digital art is presented as a means of articulating the interactive aspects of Journey’s soundtrack. Theories set out by scholars Jochen Kleres and Michel Chion—which deal with the narrativity of emotions and audiovisual meaning, respectively—are then integrated to produce the “synchretic network”: a theoretical framework for analyzing the effect of the juxtaposition of music, moving images, and an emotional response that occurs when a viewer or player engages with audiovisual art. This is followed by an analysis of a personal experience of Journey using the synchretic network to understand how the game’s music performs narrative functions. Finally, this study reflects on the synchretic network and its potential to be broadly applicable, including in the study of other audiovisual media such as film.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".