Bibliographic record
Abstract
†hank you, Rick, and good evening, ladies and gentlemen.I'm pleased to be here for two reasons: First, it's an honour to join such a stellar group of speakers and attendees.And second, the subject of this conference, Governance Reform, is crucial to Canada's future prosperity.I'd like to thank the Western Frontier International Group and the University of Manitoba's Faculty of Law for their foresight in organizing this conference.Governance reform is an issue that needs continual scrutiny and input from a wide range of stakeholders.After a full day's schedule of presentations and discussion, I suspect you don't have much cerebral room left in which to file additional information.So my remarks tonight will be brief.I'd like to begin with a statement that some people find a bit strange: President of the Treasury Board is my dream job.It's not an assignment that most politicians covet.That's because, usually, there isn't a lot of exposure.And when there is, it's often not good.So you can see why some people think it's a little odd that I really want to do this job.Mind you, I'm not saying it's easy.But it's absolutely worth doing.And, these days, it's very much concerned with significantly reforming and strengthening public sector management.This evening, I want to take a few minutes to talk about the key role of ethical management in governance reform at the federal level.Warren Buffet, probably the world's most successful investor, summed up the importance of this issue very well: "In looking for people to hire, you look for three qualities: integrity, intelligence, and energy.And if they don't have the first, the other two will kill you."Ethical management focuses on how we accomplish our policy objectives.And it rests on three pillars.The first is rules.The second pillar is leadership.Both of those issues are essential.But, given my † The Honourable Reg Alcock, P.C.,
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.068 | 0.012 |
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".