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Record W4386338121 · doi:10.1515/9781772126136

You Might Be Sorry You Read This

2022· book· en· W4386338121 on OpenAlexaboutno aff
Michelle Poirier Brown

Bibliographic record

VenueUniversity of Alberta Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceBusiness

Abstract

fetched live from OpenAlex

You Might Be Sorry You Read This is a stunning debut, revealing how breaking silences and reconciling identity can refine anger into something both useful and beautiful. A poetic memoir that looks unflinchingly at childhood trauma (both incestuous rape and surviving exposure in extreme cold), it also tells the story of coming to terms with a hidden Indigenous identity when the poet discovered her Métis heritage at age 38. This collection is a journey of pain, belonging, hope, and resilience. The confessional poems are polished yet unpretentious, often edgy but humorous; they explore trauma yet prioritize the poet’s story. Honouring the complexities of Indigenous identity and the raw experiences of womanhood, mental illness, and queer selfhood, these narratives carry weight. They tell us “You need / only be the simple / expression of the divine / intent / that is your life.” There is a lifetime in these poems.

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)0.001
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 score0.997
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1970.081

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 head0.241
Teacher spread0.219 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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