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Record W4386166769 · doi:10.59962/9780774854764-fm

Front Matter

2007· paratext· en· W4386166769 on OpenAlexaffabout
Linda Svendsen, Leonard Angel, Christianne Balk, Carol Bolt, Roo Borson, George Bow- Ering, Robert Bringhurst, Frank Davey, D Dickinson, Glen Downie, Daryl Duke, Kenneth Dyba, David Evanier, Marya Fiamengo, Michael Finlay, Dennis Foon, C. Ford, Eric Forrer, Bill Gaston, Gary Geddes, Kico Gonzalez-Risso, Elizabeth Gourlay, Paul Green, Genni Gunn, Geoff Hancock, Hart Hanson, Robert Harlow, Ernest Hekkanen, Gladys Hindmarch, Jack Hodgins, M Worth, Debbie Hewlett, Ann Ireland, Sally Ireland, Surjeet Kalsey, Lionel Kearns, Norman Klen- Man, Charles Lillard, Cynthia Macdonald, Kenneth Mcgoogan, Flor- Ence Mcneil, George Mcwhirter, Kim Maltman, Jill Mandrake, Daphne Marlatt, Seymour Mayne, Jennifer Mitton, Daniel Moses, Erin Moure, Jane Munro, R. Murray, Morgan Nyberg, Morris Panych, George Payerle, E Perrault, Karen L. Petersen, Maida Price, Linda Rog- Ers, Lake Sagaris, Andreas Schroeder, Robert Sherrin, Heather Spears, Richard J. Stevenson, Dona Sturmanis, Fred Wah, Tom Wayman, Ian H. Weir, Jim Wong-Chu, Andrew Wreggitt, Derk Wynand

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2007
Typeparatext
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFront (military)GeologyOceanography

Abstract

fetched live from OpenAlex

Words We Call Home is a commemorative anthology celebrating more than twenty-five years of achievement for the UBC Department of Creative Writing-the oldest writing program in Canada. The more than sixty poets, dramatists, and fiction writers included provide just a sample of the energy and vision the department has fostered over the years.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.074
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.9260.907

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 head0.013
GPT teacher head0.186
Teacher spread0.173 · 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".

Quick stats

Citations0
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of British Columbia Press eBooksSame topicShort Stories in Global LiteratureFrench-language works237,207