Bibliographic record
Abstract
Manitoba Law Journal (MLJ) in 2010, one of the first tasks was to determine the path that the publication would follow going forward.As we re-envisioned the goal of the MLJ, our overriding aim was to produce high-caliber and lively commentary on issues of importance to our own legal community.As part of that mandate, we decided to re-integrate "Underneath the Golden Boy" (UTGB) into the annual issues of the MLJ.Inaugurated in 2000 by Dr. Schwartz, UTGB focuses on legislation and public policy, with an emphasis on issues affecting Manitobans.While many academic law journals tend to concentrate on judicial developments, statutory changes and policy debates are topics often under-analyzed by legal academy.As usual, this year's UTGB issue includes profiles of bills enacted by the Legislative Assembly of Manitoba.Since these bills were introduced, there has been a change in government.The references to representatives of the Crown (such as ministers) are made as of the time of introduction of the relevant bill.Nora Fien discusses Bill 35, an amendment to the worker's compensation scheme in Manitoba.She does a remarkable task in discussing the often-misunderstood concept of post-traumatic stress disorder (PTSD), and the value of adding a presumption that posttraumatic stress occurred at work.Two of the most interesting elements of this paper are the comparison to other Canadian jurisdictions and the analysis of various stakeholder positions with regard to Bill 35.In his contribution, Collin Intrater tackles the important issue of bad driving, whether caused by intoxicants, distractions (such as texting and *
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.329 | 0.162 |
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".