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Record W4403648674 · doi:10.1515/9782760632226-004

Chapitre 3 Mère et sans-papiers au Québec

2014· book-chapter· fr· W4403648674 on OpenAlexaboutno aff
Alexandra Ricard-Guay, Jill Hanley, Catherine Montgomery, Francesca Meloni, Cécile Rousseau

Bibliographic record

VenueLes Presses de l'Université de Montréal eBooks · 2014
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

La préoccupation liée à une augmentation du tourisme médical périnatal a ressurgi dans le débat politique et médiatique au cours des dernières années.Le gouvernement Harper propose d'étudier la possibilité de modifier les règles de citoyenneté afin de contrer le phénomène de « tourisme obstétrique », soit lorsque des femmes enceintes provenant d'autres pays viennent au Canada dans le but d'accoucher et d'offrir la citoyenneté canadienne à leur enfant 1 .Or, derrière ce discours alarmiste qui ravive la peur de l'abus du système canadien se cache une tout autre réalité, celle des femmes migrantes sans-papiers vivant et travaillant au Québec, des femmes qui contribuent à la société et à la collectivité.Cette couverture médiatique risque de gonfler l'importance du tourisme médical au Québec et de faussement amalgamer ce phénomène à la réalité vécue par une grande partie des femmes sans-papiers.Les expériences de ces femmes -leur quotidien et leur précarité, sujets souvent éclipsés du débat politique -sont l'objet de ce chapitre.Nous nous pencherons sur les expériences des femmes ayant un statut d'immigration précaire, notamment celles qui vivent au Québec sans 1. Le Soleil, « Du tourisme obstétrique à Québec », 8 mars 2012 ; National Post, « Birth tourists' believed to be using Canada's citizenship laws as back door into the West », 18 août 2013.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0100.002
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.002

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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

Citations3
Published2014
Admission routes1
Has abstractno

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