L’art de raconter une bonne histoire : une analyse de la couverture médiatique des gangs de rue au Québec
Bibliographic record
Abstract
The media attribute a great significance to criminal events. However, those are not all reported in the same way. The media treatment of one generally depends of its sensationalism. The more impressive the event is, the more importance will be given by the media. Although street gangs have been very much present in the news content for several years, very few studies have assessed the extent to which the phenomenon is appealing to the media in relation to all criminal news. Considering the importance of media content and its impact on our society, the present study focuses on this question in order to determine whether the news about street gangs are treated differently. The sample of this study consists of 417 reports from Radio-Canada’s TV channel and Internet content, from that 210 are related to street gangs and 207 don’t bear on the phenomenon. The results suggest that the audiovisual and digital media present a more specific aspect of the phenomenon. Reports about street gangs are also more detailed and benefit from a greater mediatic treatment, regardless the medium of information used. Independently of the components that determine what make good news, the events involving street gangs and their members seem to receive a special media treatment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".