Deciding for Ourselves: Some Thoughts on the Psychology of Assessing Reasonable Expectations of Privacy
Bibliographic record
Abstract
Section 8 of the Canadian Charter of Rights and Freedoms guarantees to all Canadians the right “to be secure against unreasonable search and seizure.” Decisions regarding this section of the Charter are typically made in the context of charges against an accused, and the accumulation of these decisions defines the boundaries of the privacy interests of Canadians vis-à-vis governmental action. But while the court is focused on the privacy interests of particular individuals who have been accused of contravening the law, it is also determining the privacy rights of all Canadians. This paper explores the judgmental biases that arise naturally in such a situation. The evidence from psychological literature suggests that the degree to which government actions are viewed as intrusive (and thus compromising privacy) will be reduced to the extent that the decision maker takes a third-party perspective (search of others, not oneself) and to the extent that there is knowledge of irrelevant situational information, including the results of the potential search (i.e., whether evidence was produced) and indication of the guilt or innocence of the subject of the search. In deciding the typical section 8 case, judges find themselves in exactly these positions, and they thus run the risk of attenuated perceptions of intrusiveness. Analysis of the empirical literature suggests strategies for minimizing this bias, including considering intrusiveness from a first-person perspective and adopting an explicitly analytical stance on the specific question of whether the actions in question constitute a search or seizure.
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 | 0.077 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.009 | 0.140 |
| Scholarly communication | 0.031 | 0.036 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".