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Record W4385869367 · doi:10.59962/9780774851114-001

Acknowledgments

2007· book-chapter· en· W4385869367 on OpenAlexfundno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2007
Typebook-chapter
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsnot available
FundersUniversity of WaterlooMinistère de la Défense NationaleWilfrid Laurier UniversityUniversity of VictoriaUniversity of Calgary
KeywordsGeography

Abstract

fetched live from OpenAlex

In producing a work such as this over the course of many years, I have incurred a variety of debts.The research on which this work is based was conducted with the aid of scholarships and funding from the Ontario Graduate Scholarship Program, the Social Sciences and Humanities Research Council, and the Department of National Defence, Security and Defence Forum.I was fortunate to become part of the Tri-University Program in History at Wilfrid Laurier University, the University of Waterloo, and the University of Guelph.I benefited from the stimulating intellectual environment provided by many excellent faculty members and students in the three departments.My work in race, slavery, and imperialism with Jim Walker at Waterloo were especially important for opening my eyes to new approaches and sparking new questions in my own work.Above all I was blessed with a great friend and mentor in the person of Terry Copp.His energy and boundless intellectual curiosity pushed me onward, but his sharp questions never let me lose my focus and purpose.In many ways, this project was as much an intellectual journey for him as it was for me, and I remain thankful that he joined me for the trip.Subsequently, I have moved on to assignments at the Centre for Military and Strategic Studies at the University of Calgary, run by the industrious David Bercuson, and in the Department of History at the University of Victoria.Both these institutions and the conversations with colleagues helped me to further develop my ideas for this study.Special thanks are due to Whitney Lackenbauer and Donald Smith in Calgary and to John Lutz, Brian Dippie, Susan Ingram, and Hamar Foster in Victoria, all of whom saw a form of the manuscript, in whole or in part, and offered comments and criticisms that helped strengthen the final product.Finally, I am greatly indebted to the anonymous reviewers whose conscientious and thorough review of the manuscript forced me to face its inadequacies, to buttress its adequacies, and to derive encouragement from its strengths.

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)0.005
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.817
Threshold uncertainty score0.612

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.1830.177

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 head0.037
GPT teacher head0.209
Teacher spread0.171 · 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.

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".

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Citations0
Published2007
Admission routes1
Has abstractyes

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