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Record W2082528917 · doi:10.1353/lm.2002.0015

Literature and Obstetrics: Reading Maternal Posture in Jacques Ferron's "Little William"

2002· article· en· W2082528917 on OpenAlexaffabout
Betty Bednarski, Vivian C. McAlister

Bibliographic record

VenueLiterature and medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsParallelsNarrativeReading (process)PoliticsPosition (finance)ObstetricsLiteratureSociologyHistoryMedicineLawArtPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Jacques Ferron’s “Little William” is a story of birth and naming in a remote Quebec coastal community. Obstetrical issues and issues of cultural and political survival come together when a French Canadian doctor finds himself obliged to submit to the authority of a country midwife and deliver a baby in the so-called “English position” (or left lateral maternal posture) hitherto unknown to him. In this reading, elements of comparative obstetrical history are integrated with literary and cultural analysis, to reveal complex cross-cultural tensions, not only between French and English, but between institutional obstetrics and traditional midwifery. At the same time, attention is redirected to the figure of the story’s mother and to the “facelessness” of the birth. Parallels are drawn between Ferron’s text and scientific writing, and literary narrative is seen to mimic and at the same time call into question the narratives of obstetrical history.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.456
Threshold uncertainty score0.907

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0160.021
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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 designQualitative
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
Published2002
Admission routes2
Has abstractyes

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