Reforming the Regulation of Therapeutic Products in Canada: The Protecting of Canadians from Unsafe Drugs Act (Vanessa’s Law)
Bibliographic record
Abstract
Enacted November 2014, Vanessa’s Law amends the Food and Drugs Act to give Health Canada greater powers to compel the disclosure of information, recall drugs and devices, impose fines and injunctions, and collect post-market safety information. The Act amends seriously outdated legislation that had been in place since 1954. While the explicit goals of the Act are to improve patient safety and provide transparency, it also establishes a regulatory framework that facilitates investment in the burgeoning field of biotechnology. While regulatory reform was already on the public agenda, public awareness of litigation against large pharmaceutical firms combined with the championing of the legislation by Conservative MP Terence Young, whose daughter Vanessa died from an adverse drug reaction, pushed the legislation through to implementation. Many key aspects of the Act depend upon the precise nature of supporting regulations that are still to be implemented. Despite the new powers conferred by the legislation on the Minister of Health, there is some concern that these discretionary powers may not be exercised, and that Health Canada may not have sufficient resources to take advantage of these new powers. Given experience to date since enactment, the new legislation, designed to provide greater transparency vis-à-vis therapeutic products, may actually have a chilling effect on independent scrutiny.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".