Mistake of Age Defence in Canada: The Pressing Need to Clarify the Correct Test - Honest Belief vs. Reasonable Belief vs. Objective All Reasonable Steps vs. Quasi-Objective All Reasonable Steps Test
Bibliographic record
Abstract
Concerning the mistake of age defence in Canada under section 150.1(4) Criminal Code, RSC 1985, c. C-46 in relation to sexual offences against under-aged juveniles, the correct test for the steps analysis is objective all steps test. However, the Canadian courts have erroneously mixed it up with 3 other different tests, namely honest belief, reasonable belief and quasi-objective all steps test. The 4 tests are legally and conceptually very different, but the courts have not noticed it. There are significant implications in applying the wrong test, which will affect the factual analysis and reduce the level of protection to juveniles intended by the legislature. This article will evaluate all of the most oft-cited cases to illustrate the Courts' (including the Canadian Supreme Court in the 2017 case R v. George 2017 SCC 38) insensitivity to the legal and conceptual difference between the 4 tests. Given the inconsistent and also erroneous judicial applications of the wrong test, it is concluded that there is a pressing need to clarify the actual correct test.
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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 | 0.019 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".