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Record W6980306354

Bob Williams Book Launch: Using Power Well

2022· other· en· W6980306354 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pheromone Research and Control
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsCabinet (room)BureaucracyCorporationPower (physics)Government (linguistics)Order (exchange)
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.177
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1780.000

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.

Opus teacher head0.013
GPT teacher head0.197
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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