Between a Hunch and a Hard Place: Making Suspicion Reasonable at the Canadian Border
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines how suspicion is made reasonable at the Canadian border. It examines in local and empirical terms the ‘moment of decision’ on the frontline of border control, and the translation of this moment in the courts. It begins with a sketch of the legal regime that governs the discretion of border officers through the standard of ‘reasonable suspicion’ before considering the variety of low-level risk knowledges that coincide to make suspicion reasonable on the frontline. The ‘objectivity effect’ of the language of risk indicators (Rose, 1988) effectively obscures the multiplicity and hybridity of the ‘low-level’ knowledges at play, enhances the discretion of border officers and protects their decisions from serious scrutiny. By asking ‘who uses what knowledges, in what ways and with what effects?’ (Valverde et al., 2005: 115—116), this study responds to scholars who have appealed for the empirical specification and elaboration of risk knowledges. In so doing, this investigation also begins to unsettle the quasi-scientific representation of suspicion that prevails in the courts and urges that more specific, empirical attention be paid to how suspicion is made reasonable on the frontline.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| 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 it