Bob Williams Book Launch: Using Power Well
Bibliographic record
Abstract
In this powerful live discussion between former British Columbia cabinet minister Bob Williams and moderator Am Johal, they explored Williams’ political and economical insights through his biography, which tells the story of his unconventional life.\nIn Using Power Well, former provincial politician Bob Williams tells his atypical life story: beginning with his childhood in the working-class east end of Vancouver, Williams goes on to describe his early years as a planner in Delta, BC, his political life on Vancouver City Council and in the BC Legislature—including a major impact on the first NDP government in the 1970s—and his more recent contributions in the world of business and co-operative economics. Williams’s legacy is dotted across the physical and political landscape of BC—from the Whistler Town Centre and Robson Square to the Agricultural Land Reserve, the Insurance Corporation of BC and many projects in between. A straight shooter who refuses to mince words, Williams advocates in this highly readable and colourful book for a bottom-up approach to politics and public policy, bypassing bureaucracy in order to use power well.\nCo-presented by Nightwood Editions, Jim Green Foundation, and SFU’s Vancity Office of Community Engagement.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.143 | 0.035 |
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".