Mafia Borderland: Narratives, Traits, and Expectations of Italian-American Mafias in Ontario and the Niagara Region
Bibliographic record
Abstract
This paper will investigate narratives, traits, and expectations of Italian-American mafias in North America. The specific case study is the area of Niagara, at the border between New York State, USA and Ontario, Canada. In this context, the artricle will mainly explore narratives and traits of so-called “mafia” families in the city of Hamilton, and their apparent connections with other “mafia” groups on the other side of the borderland, in Buffalo and in Toronto.Through qualitative design adapted from grounded theory methodology with mixed data, including news stories, investigative files and interviews, this article shows how mafias in the borderland of Niagara are conceptualised as hybrid groups, employing different identity “flags”. Mafias appear isomorphic since they imitate each other's structures and (try to) obey traditional mafia rules, to adapt and survive. In line with GT methodology, this paper finally explores an emerging theoretical category, that of the mafia borderland. As a space and identity, mafia borderland helps to sketch traits and expectations of mafia groups in border areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".