Taking One Step Forward, Preventing Two Steps Back: Applying Criminal Lawyers’ Association to Invalidate Extreme Legislative Restrictions on Access to Government Information
Bibliographic record
Abstract
In 2015, the Harper federal government used an omnibus budget bill to retroactively restrict the rights of Canadians to access information concerning the federal Long-gun Registry and potentially illegal actions taken to destroy Registry records contrary to the provisions of the federal Access to Information Act. This retroactive legislative restriction of access to information rights is just the most recent example of a disturbing trend of democratic governments attempting to claw back existing access rights and thereby take 'two steps back' after having taken important steps forward along the road to greater transparency. This trend is an important reminder of the importance of constitutional protection of the right to access government information. This article revisits the Supreme Court's 2010 decision in the Criminal Lawyers' Association (CLA) case in order to explore how the constitutional protection of access to information may be applied to prevent legislatures from taking 'two steps back' along the road to transparency by protecting against extreme limitations of access rights. Part II provides a brief discussion of several examples of regressive legislative action by a number of governments seeking to restrict existing rights of access to information and an outline of the retroactive elimination of access rights imposed through the amendments to the Ending the Long-gun Registry Act (ELRA) that were passed as part of the Harper government's omnibus budget implementation legislation in 2015. Part III provides a detailed discussion of the CLA case, including a critique of the approach adopted by the Court. Finally, in Part IV, I demonstrate how the decision in CLA may be applied to invalidate the Harper government's amendments to the ELRA on constitutional grounds.
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 | 0.036 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.036 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.027 | 0.038 |
| Insufficient payload (model declined to judge) | 0.002 | 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".