Bibliographic record
Abstract
This article 1 is concerned with representations of crime in the popular print media in two regions of North America.It deals with two traditions that are the object of increasing attention by scholars in both places, though that scholarship is in its early stages.These traditions are the Mexican nota roja, a form which has reinvented itself continuously throughout the twentieth and twenty-first centuries, and the Québecois journal jaune, whose presence has diminished, since the 1960s, to the point where very few periodicals for which this designation is appropriate are still published.Each of these traditions will be discussed individually, though both will be set within a common framework through which the capacity of crime to generate a variety of print culture forms should become evident.Nota roja is a Mexican term for the chronicling of violence and crime; it has come to stand more generally for the variety of ways in which crime may be narrated within popular cultural forms (e.g., Brocca, 1993;Laurini and Diez, 1988; Piccato, 2001).While the label occasionally serves to designate crime fiction, we are using it here in its more restricted sense, to refer to newspapers and magazines specializing in true (rather than fictionalized) crime.Examples of the nota roja from the 1930s through the present include Detectives, Metropoliciaca, Nota Roja, Policía, Prensa Policiaca and Alarma.The Québecois term journaux jaunes (derived from "yellow press," a U.S. term for newspapers of low esteem) was applied to cheaply-printed newspapers or magazines which, during the 1950s and 1960s, covered crime, morality, and a wide range of sensations within Quebec.For the most part, the category consisted of magazines of varying sizes and publication frequencies, like the 1950s Montréal Confidentiel and the more long-lived Allo Police.Neither of these periodical genres was original or distinctive in an absolute sense.Indeed, both the Mexican nota roja and Québecois journaux jaunes took shape through particular assemblages of elements from the tabloid newspaper, the judiciary gazette, the fiction magazine, and more peripheral genres such as the comic book or the moral-confession magazine.The migration of these influences from one NOTA ROJA AND JOURNAUX JAUNES POPULAR CRIME PERIODICALS IN QUEBEC AND MEXICO Will Straw
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".