Les voleurs d'identité. Profil d'une délinquance ordinaire.
Bibliographic record
Abstract
Le vol d’identité a frappé 1,7 millions de personnes au Canada en 2008 et a fait 340.000 victimes au Québec l’année précédente. Malgré le volume significatif de cette forme émergente de criminalité, les connaissances dont nous disposons sur le sujet restent encore relativement limitées, particulièrement en ce qui concerne le profil des auteurs de ces crimes et leurs modes opératoires. Cette recherche, qui s’appuie sur des sources secondaires provenant en grande majorité des États-Unis, permet de mieux comprendre la dynamique du vol d’identité et de démontrer qu’il s’agit en réalité d’une forme de délinquance très diversifiée englobant des stratagèmes dont la sophistication varie grandement. Nous examinons notamment la proportion de femmes observée parmi les délinquants, le degré d’organisation de ceux-ci, les méthodes employées pour acquérir des informations personnelles et en tirer un revenu, les relations entre victimes et délinquants, les profits illicites obtenus, ainsi que la sévérité des condamnations prononcées par les tribunaux.
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.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".