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Record W4212770705 · doi:10.1080/02722011.2022.2028251

Hallmark’s Happy Crime Films

2022· article· en· W4212770705 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe American Review of Canadian Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsCriminologyArtPsychology

Abstract

fetched live from OpenAlex

This article highlights the significance of the crime genre to the resurgence of the made-for-TV-movie, especially the Hallmark Channel’s romance movies. Typical assessments of Hallmark movies as brimming with positive affect encourage us to take a closer look at the representational strategies that make such happiness possible in stories otherwise concerned with violence and death. I draw upon theories of melodrama and film to identify which experiences are considered common or shared in these predominantly white, upper-class worlds, and how they create an orientation against which guilt and justice are determined. I also situate these made-for-TV-movies in relation to discussions about the status of filmmaking in Canada, as examples of the distinct shift in emphasis in Canadian cultural policy that now sees cultural texts as products and prioritizes commercially viable—and internationally desirable—media (as distinct from “national cinema”). I combine these critical perspectives to track the ways in which Hallmark combines high body counts, low violence, and often White homogeneity into happy crime films—and what the mass production of them tells us about the present and future of filmmaking in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.088
GPT teacher head0.308
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it