Mobility, risk and closure : unaccompanied and separated child asylum-seekers and the construction of "risk identity"
Bibliographic record
Abstract
The purpose of this study is to decipher the means by which the identities of particular people, specifically unaccompanied and separated child asylum-seekers, are socially constructed as risk. Theorized here as "risk identity", this has occurred within a global context increasingly preoccupied with security. Racialized and imbued with ideological notions of citizenship, this preoccupation and the anxieties contained within it, are effectively yet unduly transferred onto individuals, who for a variety of reasons not innately related to security, are seen as undesirable. The "risk identity" classification becomes the means by Which their exclusion is legitimized and perpetuated. The increased movement of unaccompanied and separated children across international borders has occurred within this global context. Positioned largely in opposition to citizens of the industrialized west, unaccompanied and separated children seeking asylum in Canada are constructed as risk in myriad ways. Based on 13 interviews, 9 with stakeholders and 4 with youth, this study highlights four interconnected categories of risk, which serve to construct unaccompanied and separated minors as risk. These are anti-refugee discourse, anti-youth discourse, as it relates to juvenile justice discourse, prejudicial attitudes and the fear of difference, and securitization discourse.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| 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".