Bibliographic record
Abstract
Paul Boothe served as Canada’s senior associate deputy minister of industry during the Global Financial Crisis (GFC) of 2007–2009. Boothe led the Canadian federal government’s negotiation team during the restructuring talks with Chrysler and General Motors (GM). He also negotiated with the Canadian Auto Workers (CAW), a union that included Tier 1 auto parts suppliers for all the major auto manufacturers worldwide. Canada aligned with the United States government to rescue the auto manufacturers and provided 20% of the funding to rescue the corporations and suppliers. From 2004 to 2005, Boothe served as the associate deputy minister of finance and Group of Seven (G-7) deputy for Canada; after the GFC, he was deputy minister of the environment from 2010 to 2012. In 2016, Boothe was awarded the Order of Canada, the nation’s highest civilian honor, for his contributions to shaping Canadian economic and fiscal policy. He currently teaches in the executive program at the Ivey Business School at Western University in Ontario. This Lessons Learned summary is based on an interview held with Boothe on May 9, 2022.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".