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Record W4385871635 · doi:10.59962/9780774853576-002

Acknowledgments

2007· book-chapter· en· W4385871635 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Many debts are incurred in the creation of a collection of essays such as this one.We would first like to thank Laura Macleod, the Toronto editor for UBC Press whose belief in the project was important from the beginning.When, first, one of us decamped and headed across the continent to Victoria and, a year later, the other crossed the sea to Indonesia, our delightful meetings with Laura had to be replaced by e-mail and phone calls.But her faith never wavered.We are grateful for her continued confidence in our work, as well as her unfailingly fine judgment and good humour.Second, thanks are due to the many people who assisted with the research for this book.National, provincial, municipal, and university archivists and librarians in Canada, the United States, and Great Britain were enthusiastic and helpful.We thank in particular the librarians and archivists who assisted the editors and authors at Acadia, McGill, and Queen's Universities; at the Universities of Toronto, Saskatchewan, and British Columbia; at the Smith College Archives in Northampton, Massachusetts; and at the National Archives, the Archives of Ontario, the Metropolitan Toronto Library, and the City of Toronto.Their knowledge and dedication were essential to our task.In addition, researchers and support staff at the Ontario Institute for Studies in Education, Carleton University, and the University of Victoria have supported our work in many ways.We want especially to thank Paula Bourne, Elizabeth Fear, and, last but not least, Alyson King, whose skills have added a great deal to the completed volume.Also important to the final product were the interest and insights of the anonymous reviewers appointed by UBC Press and the Aid to Scholarly Publications Programme.Their prompt reports and even-handed criticisms were invaluable.Finally, we would like to thank our families.Guthrie and Theo, not to mention their wonderful parents, Douglas and Shirley, have sustained and vastly improved the humour of their historian grandmother during many

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)0.006
metaresearch head score (Gemma)0.039
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: Other
Teacher disagreement score0.170
Threshold uncertainty score0.569

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.1700.130

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 head0.046
GPT teacher head0.238
Teacher spread0.192 · 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".

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Citations0
Published2007
Admission routes1
Has abstractyes

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