The 'Bogus' Refugee: Roma Asylum Claimants and Discourses of Fraud in Canada's Bill C-31
Bibliographic record
Abstract
The passage of Bill C-31 into Canadian law in June 2012 is part of a discourse created around refugees by the current Government of Canada. Refugees are divided into “good and proper” refugees who live in camps abroad, and the “ fraudulent and bogus” refugees who claim asylum at the Canadian border. The new act, Bill C-31 or Protecting Canada’s Immigration System Act, is analyzed with respect to changes that will result in the systematic exclusion of certain groups of asylum seekers from Canada, based on these discourses of “bogus” and “fraud,” even though these groups may include genuine refugees. Drawing on the case of Czech Roma refugee claimants who come to Canada from Europe, this article shows how the Roma come to stand for the perfect “bogus” refugee — a person who wants to cheat the benevolent Canadian system without having grounds for a successful refugee status application. A critical look at the legislation provides new insights into the relations between governmentality and the regimes of citizenship, with the state performing its power in increasingly spectacular ways. Refugees act as the abject Other that legitimizes, legalizes, and reaffirms such state interventions. L’adoption du projet de loi C-31 en juin 2012 fait partie d’un discours cree par le gouvernement actuel du Canada autourdesrefugies. Ceux-cisontdivisesen «bonsetjustes» refugies qui vivent dans des camps a l’etranger et refugies «bidon et frauduleux» qui demandent l’asile a la frontiere canadienne. La nouvelle loi, le projet de loi C-31 ou Loi visant a proteger le systeme d’immigration du Canada, est analysee en fonction de changements qui se traduiront par l’exclusion systematique du Canada de certains groupes de demandeurs d’asile, sur la base de ces notions de «bidon» et «fraude», meme si ces groupes peuvent comprendre de veritables refugies. S’appuyant sur le cas de demandeurs d’asile roms tcheques venus d’Europe au Canada, cet article montre comment les Roms en viennent a incarner le refugie «bidon» ideal — quelqu’un qui veut abuser de la bien-veillance du systeme canadien en deposant une demande de statut de refugie sans fondement. Un regard critique sur le projet de loi apporte un nouvel eclairage sur les relations entre la gouvernementalite et les regimes de citoyennete, ou l’etat exerce son pouvoir de facon de plus en plus spectaculaire. Le refugie tient lieu d’Autre abject qui legitime, legalise, et reaffirme les interventions de l’Etat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".