MétaCan
Menu
← Back to cohort
Record W6926208383 · doi:10.20383/103.01179

Portrait de l'empowerment des personnes enceintes au Québec dans leur suivi prénatal

2025· dataset· fr· W6926208383 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMedical careCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Abstract

fetched live from OpenAlex

L'empowerment dans un contexte prénatal, bien que plébiscité, peut rencontrer des défis dans son application, notamment avec la médicalisation des soins prénataux. Face à ces défis, nous avons voulu dresser un portrait du niveau d'empowerment des personnes enceintes au Québec et identifier les facteurs susceptibles de l'influencer, dont les technologies numériques. Nous avons mené une enquête quantitative anonyme auprès de personnes enceintes ou ayant accouché au cours de la dernière année au Québec. Les participants ont répondu à des questions sociodémographiques, ainsi qu'à des questions sur leur grossesse et leurs soins prénataux. Elles ont ensuite été interrogées sur leur compréhension et leur perception du concept d'empowerment. On leur a également demandé de remplir l'échelle d'empowerment de Klima et de ses collègues, de donner leur opinion sur l'influence des facteurs sur leur processus d'empowerment, leur utilisation des ressources pour soutenir leur empowerment.

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)0.001
metaresearch head score (Gemma)0.003
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.034
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.004

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 head0.030
GPT teacher head0.313
Teacher spread0.283 · 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
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOpen MIND→French-language works237,207→