Bibliographic record
Abstract
This is a film review of Dead Snow 2: Red vs. Dead (2014), directed by Tommy Wirkola. Author Notes Jodi McDavid is an instructor in Folklore and Gender & Women’s Studies at Cape Breton University. She earned her BA at St. Thomas University (New Brunswick) and her MA and PhD from Memorial University of Newfoundland. Her PhD dissertation was on anticlericalism in folk and popular culture. Her current research interests include vernacular religion, the folklore and folklife of children and adolescents, and gender and women’s studies. This sundance film festival review is available in Journal of Religion & Film: http://digitalcommons.unomaha.edu/jrf/vol18/iss1/27 Dead Snow 2: Red vs. Dead (2014) directed by Tommy Wirkola Midnight Picking up where Dead Snow left off, Dead Snow 2 adds another cult film to the zombie genre. The original film was noted for its use of Nazi who appeared in the present day—once teenagers uncovered their horde of Jewish gold, of course. Although the first installment takes place in a rural atmosphere, the second moves the action into more urban settings, and the main character meets a whole group of new friends. The original film was filled with gore, as is the second. Neither film is in the torture porn category of horror, but would more appropriately be categorized as B slasher films. One might suspect that religion would have little to do with this film, however, there are a number of taboos that are broken, and a fair number of them have to do with religion. When the German zombies begin to create more zombies, their first convert is a lecherous Priest. The zombies are created through resurrection, and there is a blatant disregard for the body and natural law. Other taboos are broken; our hero inadvertently kills a young boy in a tragic (although somewhat hilarious) manner. The last taboo of the film is too central to the film to discuss. But it involves a churchyard. And I will leave it at that.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".