“Gang” as Empty Signifier in Contemporary Canadian Newspapers
Bibliographic record
Abstract
The word gang appears frequently in newspapers. The meaning of this term, however, varies greatly depending on context. This study examines its different significations in the top-selling English-language newspapers in Canada. Taking almost 3,900 occurrences of the term and its variants (gangs, ganging, and ganged) in the Globe and Mail, the Toronto Star, the Vancouver Sun, and Montreal's Gazette, the authors analyse how journalists deploy the concept of gangs to describe diverse subjects from vandalism by teenagers to extortion by organized crime syndicates to terrorist plots by religious extremists as well as simply groups of friends or acquaintances with no criminal connections. Using Ernesto Laclau's concept of the empty signifier as the main theoretical framework, the authors argue that “gang” has been emptied of its meaning and, while its current uses are not necessarily indicative of conspiratorial or ideological strategies, this ambiguity risks being appropriated within hegemonic political discourses if not questioned and reassessed by journalists and readers. The authors conclude by suggesting ways to combat this problem of ambiguity and highlight the political implications that future researchers may explore in relation to mediated representations of crime.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".