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Record W4379804887 · doi:10.1353/fro.2017.a669206

Slumbering Woman

2017· article· en· W4379804887 on OpenAlexaboutno aff
Carol Lipszyc

Bibliographic record

VenueFrontiers A Journal of Women Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryScholarshipArtArt historyHistoryVisual artsLiteratureMedia studiesSociologyLawPolitical science

Abstract

fetched live from OpenAlex

Slumbering Woman Carol Lipszyc (bio) See this woman who dons injury like a vintage mink stole, weathered tail wrapped around her shoulders across her chest. She lives where tenderness follows the bruising word where tell- tale wounds leave an indelible print. Sleeps where night is mercenary— regrets and remorse their double henchmen. Odd, how in the dark, regrets find refuge— come daylight they trail her in shadow steps. Should her heart open its trap door tap like a child in the play- penned hour she will answer— If only I could, I would . . . her refrain grazing her slumbering heart. [End Page 209] Carol Lipszyc carol lipszyc’s book of poetry, Singing Me Home (2010), and book of short stories on children and adolescents in the Holocaust, The Saviour Shoes and Other Stories (2014), were published by Inanna Publications. In fall 2017 her anthology of poems on the heart, The Heart Is Improvisational, will be published by Guernica. Carol earned her doctorate in education at the University of Toronto, OISE. She has published scholarship in arts-based education journals in Australia, New Zealand, England, and Canada. Her Literacy/ESL Reader with chants, People Express, was published by Oxford University Press. Carol is currently an associate professor in the English Department at SUNY, Plattsburgh. “Slumbering Woman” discloses a woman unable to open to the potential of love, wearing injury like a daily habit. Her past carries its weight, whether the subject of the poem is fully cognizant or unaware of the forces that have shaped her. Copyright © 2017 Frontiers Editorial Collective, Inc

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.270
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

Explore more

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