The Dark Knight’s Many Stories: Arkham Video Games as Transmedia Pathway
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
This article examines the Batman Arkham video game series (Rocksteady/WB Montreal, 2009-2015) as part of a wider transmedia franchise that encompasses comic books, films, merchandise and multiple animated and live-action television series. It will be posited that the video game series is a successful entry point for non-fans into this ever-expanding transmedia universe. Batman: Arkham Asylum (2009), the first of the series, was critically acclaimed and established the gameplay, mechanics, and rules for the sequels Arkham City (2011), Arkham Origins (2013) and Arkham Knight (2015). Gameplay mechanics are linked to ‘player agency,’ i.e. how the user controls the avatar within the game environment. Player agency is somewhat restricted in the series; however, this will be argued to be a benefit for audiences. There are somewhat ludic conditions that can either be beneficial or detrimental for the player, to ensure they learn from failure. This essay will further argue that players accumulate a wider understanding of the Batman universe by collecting artefacts as they deviate from the central narrative. The player unearths character biographies and interview tapes that are based on the character’s extensive history and, thus, provide a gateway into the transmedia world of Batman.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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