Bibliographic record
Abstract
ill 17, The Securities Amendment Act,l was given Royal Assent in the Manitoba Legislature on 13 June 2006.Bill 17 went through its life cycle in a relatively short period of time considering the vast amount of amendments it proposed.It was introduced for first reading on 22 November 2005 and given Royal Assent in less than seven months.Bill 17 moved quickly because its readings in the legislature and the parliamentary committee meeting where it was reviewed were but formal steps in a process that had started long before.Bill 17 introduced amendments to the existing Securities Act 2 as a part of an overall scheme set in place by 12 provinces and territories to make improvements to the securities regulatory framework in Canada.3 In recent years, there has been heated debate in this country over whether our securities framework should be overhauled to resolve the differences between the many regulatory bodies in the industry and whether a more uniform securities market should be created.In 2003, the provinces and territories implemented the Provindal~Territorial Securities Initiative to begin the process of harmonizing securities laws across the country.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.021 |
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".