p 1 The false promise of gun control Submitted to The Fraser Forum
Bibliographic record
Abstract
On January 1, 2003, all firearms in Canada have to be registered. After that date, anyone who possesses an unregistered firearm becomes an instant criminal. The punishment is up to 10 years in jail. We’re supposed to believe that this will make us safe from violence. But will it? Canada appears to be following England’s approach to gun control. England not only has required the registration of rifles and shotguns, but in 1997, it banned all handguns as well. Have the new gun laws made England safer? Canadians who believe that more guns mean more crime will be shocked by the revelations in Joyce Lee Malcolm’s latest book, Guns and Violence,The English Experience.1 The author is a Professor of History at Bentley College in Massachusetts. It is an article of faith for many that English firearm regulations, the toughest of any democracy, are responsible for producing a low rate of violent crime. Professor Malcolm’s careful analysis debunks this myth. Professor Malcolm exposes two problems with the assumption that access to firearms underlies criminal violence. First, prior to the First World War, firearms
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.024 | 0.016 |
| Insufficient payload (model declined to judge) | 0.077 | 0.018 |
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".