Symbolic Mediation in the Red Foot Saga
Bibliographic record
Abstract
Submetido em 13 de março e aprovado em 10 de maio de 2015. Abstract: The Canadian/Brazilian production Red Foot Saga (RFS) is a narrative videogame about the cultural memory of Londrina city. Our goal is to examine the role of symbolic mediation through the videogame’s nonverbal language. Our RFS analysis reveals how the interactions with the symbols in the game world allows the player to construct either evocative or enacted stories inspired by Londrina’s cultural and territorial history. In this article, the authors elaborate that the RFS nonverbal language used for symbolic mediation is composed of the virtual places, the identity markers, and the player’s performance. After that, the authors illustrate that symbolic mediation requires adaptation and recoloring. While the principal goal of this article is to articulate the evocative and the enacted type stories that occur in RFS, according to Henry Jenkins ’ theory (2004), the last part of the article is a reflection upon the memory adaptation theme in the RFS project and the cross-cultural game design ideal.
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 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 | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".