MétaCan
Menu
Back to cohort
Record W7068284296

How To Save Canada

2023· other· en· W7068284296 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2023
Typeother
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyPoliticsMetropolitan areaAdministration (probate law)AuthoritarianismJournalismWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Rob Goodman was a congressional staffer in the US and as a rising authoritarian movement brought America to the brink of a coup, he did what all Americans threaten to do when they are fed up with their country: he moved to Canada. Now an Assistant Professor in the department of Politics and Public Administration at Toronto Metropolitan University, he has an urgent warning for his adopted country.Jesse sits down with Rob to talk about his new book, \\"Not Here: Why American Democracy Is Eroding and How Canada Can Protect Itself.\\"Host: Jesse Brown Credits: Tristan Capacchione (Audio Editor and Technical Producer), Bruce Thorson (Senior Producer), Annette Ejiofor (Managing Editor), Karyn Pugliese (Editor-in-Chief)Further Reading: Not Here: Why American Democracy Is Eroding and How Canada Can Protect Itself, by Rob Goodman - Simon & SchusterSponsors: Douglas, Elijah Craig, IndochinoIf you value this podcast, support us! You'll get premium access to all our shows ad free, including early releases and bonus content. You'll also get our exclusive newsletter, discounts on merch at our store, tickets to our live and virtual events, and more than anything, you'll be a part of the solution to Canada's journalism crisis, you'll be keeping our work free and accessible to everybody.You can listen ad-free on Amazon Music-included with Prime. Hosted on Acast. See acast.com/privacy for more information.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.276
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1530.023

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 head0.024
GPT teacher head0.237
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of Miscellaneous Information (Royal Gardens Kew)Same topicScientific Computing and Data ManagementFrench-language works237,207