The Supreme Court of Canada Long-Gun Registry Decision: The Constitutional Question Behind an Intergovernmental Relations Failure
Bibliographic record
Abstract
In 2012, Parliament repealed the federal law that had established a mandatory long-gun registry. The law to repeal the long-gun registry also provided for the destruction of the data contained therein. Quebec, however, expressed its intention to establish its own gun-control scheme and asked the federal government for its data on long-guns owned by residents of Quebec. When the federal government refused to turn over the data from the long-gun registry, despite the fact that Quebec government offi cials had access to the data while the long-gun registry was in operation, Quebec challenged the constitutionality of the federal law providing for the destruction of the data and sought an order requiring the federal government to turn over the data to Quebec. Th e federal government’s refusal to participate in an act of intergovernmental cooperation began a three-year round of constitutional litigation that concluded in March of 2015 with a split decision of the Supreme Court of Canada.
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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.040 | 0.017 |
| Scholarly communication | 0.027 | 0.005 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.028 | 0.029 |
| Insufficient payload (model declined to judge) | 0.008 | 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".