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Senator Stanley Haidasz: A Statement for All Canadians

2017· article· en· W4248350076 on OpenAlexaboutno aff
Radosław Misiarz

Bibliographic record

VenuePolish American Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceCitationIconWorld Wide WebComputer sciencePolitical scienceInformation retrieval

Abstract

fetched live from OpenAlex

Book Review| October 01 2017 Senator Stanley Haidasz: A Statement for All Canadians Aleksandra Ziółkowska-Boehm. Senator Stanley Haidasz: A Statement for All Canadians, (Montreal: Polish Institute of Arts and Sciences in Canada, 2014). 214 pp. ISBN 978-0-986-8851-1-2. Radosław Misiarz Radosław Misiarz Chicago Search for other works by this author on: This Site Google Polish American Studies (2017) 74 (2): 107–108. https://doi.org/10.5406/poliamerstud.74.2.0107 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Radosław Misiarz; Senator Stanley Haidasz: A Statement for All Canadians. Polish American Studies 1 January 2017; 74 (2): 107–108. doi: https://doi.org/10.5406/poliamerstud.74.2.0107 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveUniversity of Illinois PressPolish American Studies Search Advanced Search The text of this article is only available as a PDF. Copyright 2017 by the Board of Trustees of the University of Illinois2017 Article PDF first page preview Close Modal Issue Section: Reviews You do not currently have access to this content.

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)0.003
metaresearch head score (Gemma)0.014
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0050.002
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.1690.100

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 head0.050
GPT teacher head0.368
Teacher spread0.318 · 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
Published2017
Admission routes1
Has abstractyes

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