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Record W4385598611 · doi:10.59962/9780774862790-001

Acknowledgments

2020· book-chapter· en· W4385598611 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Our first co-editing experience together (which became the 2012 collection, A Sisterhood of Suffering and Service) was so positive that, even before we finished the project, we talked about doing it again.In the end, we took a fiveyear break, then tore off the dustcovers and cranked up the editorial machinery once more.It's been even more enjoyable the second time around.We work well together because we divide-to-conquer, pick up the slack during hectic or stressful periods of each other's lives, remember things the other has forgotten, and laugh a lot.It's a treat to watch half-baked ideas and "very drafty drafts" transform into smarter, more stylish versions of themselves as they travel back and forth between us.But regardless of whether Sarah was living in Ontario or New Brunswick, Amy in Alberta was always too far away for a casual afternoon chat over coffee.Our first big thank you therefore needs to be directed at Science and Technology for all the digital and telecommunications inventions that have allowed this Arts and Humanities partnership to flourish.Fittingly, our one and only in-person meeting about the book, in the summer of 2018, took place in the Brutalist concrete splendour of Weldon Library, at our mutual alma mater, Western.So, thank you, Science.(Just don't get uppity about it. The Arts matter, too!)The research, writing, editing, and production of this book took place against a backdrop of broken bones and health complications, relationships formed and ended, demanding jobs and major career changes, geographical relocations, the joys and heartbreaks of parenthood and family relationships, and the varied mini-dramas of daily life.The authors and editors alike have struggled to find time, space, and quiet simply to think, let alone to say something new and important, and to say it well.For these reasons, we would like to thank the authors whose work is represented in this volume for carving out a bit of space in their lives for this joint endeavour, and for making it a priority when it needed to be.We know it has not always been easy, and that makes us appreciate it even more.There are good reasons some scholars want no part of edited collections or other collaborations: having to co-ordinate schedules, negotiate deadlines, wait for others to finish their work, buy into a collective vision, and take practical steps to integrate one's work into a larger entity can be annoying and frustrating.

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)0.007
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.612
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0070.004
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.3880.298

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 head0.044
GPT teacher head0.173
Teacher spread0.129 · 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; the direct Gemma label and the distilled Codex classifier 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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