Bibliographic record
Abstract
The research is concerned with presenting and explaining the rule of excluding illegal evidence in Canadian law, as the Canadian legislator has adopted the legitimacy of accepting any evidence of proof regardless of the legitimacy of obtaining it or not, but has set conditions and restrictions for it, including that it be specific to or related to the dispute presented to the judge, and has given the judge discretionary authority to exclude evidence that has no value in the subject. In the research, we have shown the position of the Canadian legislator on excluding illegal evidence, and it has become clear that in jurisprudence and judiciary, it does not reject illegal evidence completely, but rather has its own conditions for its status, which is to leave the matter of assessing acceptance to the judge, either the evidence is in favor of the case, or the evidence is not important to the case, as the judge’s discretionary power is what determines the extent of acceptance or not, and even if the researcher rejected this opinion due to the waste of the rights stipulated in the constitutions and charters to the extent of preserving the private life of the person and not intruding on it under any name, this opinion has a convincing side when they acknowledged that accepting this evidence despite its illegality saves an innocent person from punishment and protects society from a criminal at large due to the lack of legal conditions in the evidence presented to convict him, even if the whole matter is in the hands of the judge. The research attempted to present this topic in an organized and smooth manner that benefits researchers in this field.
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 | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.023 | 0.034 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".