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Record W4403836970 · doi:10.18192/aporia.v14i2.7060

Pourquoi certaines femmes choisissent d’accoucher sans assistance professionnelle ? Une recension systématique des écrits

2024· article· fr· W4403836970 on OpenAlexafffundvenueabout
Audrey Bujold, Christine Gervais, Pierre Pariseau‐Legault

Bibliographic record

VenueAporia · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsUniversité du Québec en Outaouais
FundersRéseau de recherche portant sur les interventions en sciences infirmières du QuébecUniversité du Québec en Outaouais
KeywordsSociologyHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les accouchements non assistés (ANA) font référence au fait que certaines femmes choisissent de vivre un accouchement en l’absence de professionnel·les de la santé alors que des structures médicales sont normalement disponibles pour les soutenir si elles le désirent. Au Québec et ailleurs dans la francophonie, à notre connaissance, aucune recension des écrits n’a été publiée malgré les questionnements croissants concernant ce phénomène. Cet article vise ainsi à présenter les résultats d’une recension systématique des écrits (n=32) qui porte précisément sur les ANA. Nos résultats décrivent le profil sociodémographique des femmes qui choisissent les ANA, les motivations et le processus décisionnel lié à ce choix, les risques socioculturels auxquels ces femmes sont exposées et la place qu’occupent les réseaux socionumériques dans ce processus décisionnel. Afin d’élargir notre compréhension de ce phénomène, nos résultats sont ensuite mis en dialogue avec d’autres situations de non-recours aux services de santé et d’autres pratiques familiales alternatives.

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)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.157
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.050
GPT teacher head0.351
Teacher spread0.301 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes4
Has abstractyes

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