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Record W4411985672 · doi:10.15353/cjds.v12i2.1014

Early twentieth century women reading through disability and illness: Letters to Canadian novelist Ralph Connor

2023· article· en· W4411985672 on OpenAlexaffvenueabout
Grace O'Hanlon

Bibliographic record

VenueCanadian Journal of Disability Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsReading (process)Reading disabilityPsychologyHistoryPsychoanalysisGender studiesGerontologyPsychiatrySociologyMedicineDyslexiaPolitical scienceLaw

Abstract

fetched live from OpenAlex

Ralph Connor was a well-known novelist in the first decade of the twentieth century. Many people read his popular fiction novels around the world. Perhaps owing to his popularity and penchant for keeping correspondence, his collected papers, held the Archives and Special Collections at the University of Manitoba in Winnipeg, Canada, include over six hundred fan letters. I examined these letters with the intention of exploring women’s responses to popular fiction of the era and the reasons they were reading. As I read the letters, a recurring theme emerged in letters penned by women: they described the role of reading in their lives in relation to their personal experiences with disabilities and chronic illness. Others wrote about the experience of reading to their mothers, sisters, or friends with disabilities. These fan letters are the voices of women with disabilities who were relegated to the margins of society. Ultimately, the letters reveal the role of reading as a leisure activity, a vocation, and a social outlet in the lives of early twentieth century women who identified themselves as invalids, shut-ins, and bedbound.

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)0.004
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.146
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0750.023
Scholarly communication0.0120.004
Open science0.0030.005
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0080.001

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 head0.031
GPT teacher head0.286
Teacher spread0.255 · 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
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
Published2023
Admission routes3
Has abstractyes

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