Bibliographic record
Abstract
Marvel Cinematic Universe (MCU) films provide a recognition of the prevailing crises of our time along with a clear sense of good and evil and that good will prevail, the fantasy that someone will come along to bring us back to the imagined certainty of the liberal status quo. The polarization of our time is reflected within Marvel movies as they (conditionally) critique colonialism, imperialism, patriarchy, and greed, only to individualize their (re)solutions. Black Panther (2018) and Captain Marvel (2019) are the focus of this case study due to their appeal beyond even MCU fans and their focus on two forms of oppression that are often represented as dominant structures of our time: white supremacy and patriarchy. The MCU films foreground challenges to dominance in order to neutralize those critiques; the films narrativize liberal triumph by appropriating its opposition. The adaptation of liberalism in the MCU is to make its own critiques visible and then contain them—a double move that accounts for the immense cultural purchase of these films.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".