Bibliographic record
Abstract
T he claim that superhero comics culture is a modern religious and/ or mythopoeic expression has been repeated so often by academic observers of pop culture over the years, it has assumed the dimensions of a modern myth in its own right.It has provided the driving thesis behind a chorus of academic works that has mushroomed steadily over the decades, 1 and inspired a considerable trend in teaching about religion in North American universities.2 Critically evaluating this claim that superhero comics culture is in e ect a modern religious or mythopoeic expression can, though, feel at times like reading comics produced by M.C.Escher, since superhero comics "mythology" so often includes elaborate homage to (and exuberant plagiarism of) real-world religions and myths, including the religions and myths held sacred by the heroes themselves.3 To complete 1 From Umberto Eco's "The Myth of Superman," trans.Natalie Chilton, Diacritics 2, no. 1 (Spring, 1972): 14-22 to Andrew R. Bahlmann's The Mythology of the Superhero (Je erson, NC: McFarland, 2016), such scholarly studies have grown steadily in terms of both quantity and sophistication.See Sections 1 and 2 below for representative works.2
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.090 | 0.028 |
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".