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Record W4380234800 · doi:10.1515/9780228004813

Little Resilience

2020· book· en· W4380234800 on OpenAlexaboutno aff
Eli MacLaren

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2020
Typebook
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Computer sciencePsychologyPhysics

Abstract

fetched live from OpenAlex

The Ryerson Poetry Chap-Books were a landmark achievement in Canadian poetry. Edited by Lorne Pierce, the series lasted for thirty-seven years (1925-62) and comprised two hundred titles by writers from Newfoundland to British Columbia, over half of whom were women. By examining this editorial feat, Little Resilience offers a new history of Canadian poetry in the twentieth century. Eli MacLaren analyzes the formation of the series in the wake of the First World War, at a time when small presses had proliferated across the United States. Pierce's emulation of them produced a series that contributed to the historic shift in the meaning of the term "chapbook" from an antique of folk culture to a brief collection of original poetry. By retreating to the smallest of forms, Pierce managed to work against the dominant industry pattern of the day - agency publishing, or the distribution of foreign editions. Original case studies of canonical and forgotten writers push through the period's defining polarity (modernism versus romanticism) to create complex portraits of the author during the Depression, the Second World War, and the 1950s. The stories of five Ryerson poets - Nathaniel A. Benson, Anne Marriott, M. Eugenie Perry, Dorothy Livesay, and Al Purdy - reveal poetry in Canada to have been a widespread vocation and a poor one, as fragile as it was irrepressible. The Ryerson Poetry Chap-Books were an unprecedented initiative to publish Canadian poetry. Little Resilience evaluates the opportunities that the series opened for Canadian poets and the sacrifices that it demanded of them.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.194
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.008
Scholarly communication0.0100.005
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1250.038

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 head0.022
GPT teacher head0.282
Teacher spread0.260 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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