Nothing Plus Nothing Equals... Something? A Proposal for FLIR Warrants on Reasonable Suspicion
Bibliographic record
Abstract
Over a series of decisions, the Court has been backing itself into a corner with its section 8 jurisprudence. Section 8 protects against unreasonable searches. Since the earliest ruling on the section in Hunter v. Southam, searches are prima facie unreasonable if they take place without a warrant. Thus, before conducting a search, police must have a warrant. Before getting a warrant, police must have information about the accused. Obtaining information about the accused probably involves conduct that qualifies as a search. Thus for example in K. v. Kokesch, R. v. Wiley, and R. v. Plant, perimeter searches, conducted in order to get grounds for seeking a warrant, were themselves warrantless searches which violated s. 8. In order to get warrants to conduct those searches, police would need already to have reasonable grounds to believe that the search would produce evidence. That evidence in turn would have to consist of personal information likely to invoke a reasonable expectation of privacy. Barring reliable unsolicited tips arriving at the police station, this regression is potentially endless.
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 | 0.033 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.040 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.031 | 0.023 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".