Reforming Borders of the Imagination: Diversity, Adaptation, Transmediation, and Incorporation in the Global Disney Film Landscape
Bibliographic record
Abstract
The transmediation involved in recent Walt Disney Company productions including A Wrinkle in Time, Black Panther, Thor: Ragnarok, Coco, and Moana engage with a process of visualizing the nonvisual in ways that have heretofore differed from past Disney offerings. These films respond to calls for increased diversity, unlocking the potential of imagined spaces on a global scale. Although it addresses postcolonial identity politics that are both salient and fraught in the current geopolitical climate, such diversity nevertheless serves Disney’s corporate interests, (re)producing a colonizing progression decentralized from the nation-state but rooted in projection of culture. As Disney adapts new narratives, it also engages in a process of incorporation, absorbing these narratives into the larger framework of the overarching corporate structure of the “magic kingdom”—intended to designate a cultural home for childhood, imagination, and reminiscence of how things were and what they might become. I contend that Disney’s incorporation of new narratives extends greater access to imaginary spaces while producing a homogenizing effect on global media culture.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".