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Record W4382449475 · doi:10.1515/9780773553705

Inside Politics

2018· book· en· W4382449475 on OpenAlexaboutno aff
L. Ian MacDonald

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2018
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

If journalism is the first draft of history, it’s equally important to see how the work stands the test of time. If the writing isn’t prescient and perspicacious, it doesn’t meet that test. This collection of columns and articles by L. Ian MacDonald - a sequel to Politics, People & Potpourri - meets that test. Much has happened in the politics of Canada and Quebec, as well as to the leaders who have defined and shaped the first two decades of the twenty-first century, since the first collection was published in 2009. The successful election campaigns of Harper and Trudeau form the political bookends of the present decade in Canada and the opening chapters of the book. Between these governments, there are the events, personalities, and issues that have shaped the political narrative and policy debate, from fiscal frameworks to clean energy and pipelines, from the Senate expense scandal and democratic reform to national security at home and the mission against ISIS abroad. In his columns, and longer pieces from Policy Options and Policy magazines, MacDonald provides clear-minded commentary on political issues salient to all Canadians - including the election of Donald Trump in the United States. He also profiles a diverse group of political figures, and writes moving tributes to departed, nationally respected figures such as Jean Béliveau, Jim Flaherty, Jack Layton, and Tom Van Dusen. This intelligent and entertaining collection presents MacDonald at his best, and offers a captivating view of Canadian politics and life.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.997
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0200.008
Open science0.0010.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.1110.053

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMcGill-Queen's University Press eBooks→Same topicCanadian Identity and History→French-language works237,207→