Securitization and criminalization: an analysis of the Temporary Resident Biometrics Program (TRBP)
Bibliographic record
Abstract
<p>The implementation of the Temporary Resident Biometrics Program (TRBP) in Canada and its purpose to enhance national security raises many questions. Through the collection of individuals’ unique biological data, certain foreign nationals are classified as potential threats.</p> <p>Using legislative texts, this qualitative study examines the objectives and implications of the program. Through government discourses, the TRBP identified as part of a securitization move constructs immigrants and refugees as “criminals†, leading to exclusionary immigration legislation. While questioning whether or not the use of biometrics in Canada serves a legitimate national purpose in immigration policy, this study reveals the unjustifiable discriminatory implications of adopting a securitization strategy that is part of a global trend.</p> <p><br></p> <p>Key words: Securitization, biometrics, criminalization, Temporary Resident Biometrics Program</p>
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".