Playing as a mutant in a virtual world: understanding overlapping story worlds in popular culture video games
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract On the basis of interview data with a video game designer, this author team explores the nuances of stories and story worlds in video games as complex multimodal, compositional processes that can be harnessed to our understandings about contemporary literacy learning. How we enter, exit, mediate and transmediate stories across media channels has been naturalised into the ways that we view and understand media texts, yet as literacy scholars interested in the role of media and literacy learning and teaching, do we actually understand the mediational practices and logic enacted when a story moves from a film to a video game? This article goes some way in extrapolating the process of story transformation when a ‘canonical’ story moves from a film text to a gaming text. By using X‐Men Destiny as our exemplar, the article classifies and attends to three overlapping worlds that are negotiated when approaching adapted video games: a canonical mythic universe , the adapted game world and the story world of a learner , in order to enable the harnessing of video game practices for literacy contexts.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it