Canada's 1995 Gun Control Legislation: Problems and Prospects
Bibliographic record
Abstract
We discuss Canada's universal gun registration legislation (Bill C-68), passed in December 1995. It has been plagued by a variety of problems: delays in coming into force, huge cost overruns, need to cut fees to encourage compliance, massive problems with its computer systems, stubborn resistance by anti-control groups, and the fact that eight of 10 provinces refused to participate in administering the new law. To hide the overruns, the federal government resorted to back door financing. While the latest deadline for registration of all long guns and hand guns was July 1, 2003, it is not clear that universality was achieved. For one thing, the official estimate of the stock of guns is almost far below the actual number of guns in private hands. We explain that, like almost all previous gun control legislation in Canada, Bill C-68 reflects a persistent kultur kampf and opportunistic behaviour by politicians.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.013 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".