MétaCan
Menu
Back to cohort
Record W3122765476

L'activite feminine dans le pays d'origine et les salaires des immigrantes au Canada

2015· article· fr· W3122765476 on OpenAlexaboutno aff
Feng Hou, Kristyn Frank

Bibliographic record

VenueDirection des études analytiques : documents de recherche · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Des etudes anterieures ont revele une forte association entre le taux d'activite feminine dans le pays d'origine et l'activite des immigrantes dans le pays hote. Cette relation est interpretee comme le resultat de l'influence persistante des attitudes a l'egard des roles sexospecifiques dans le pays d'origine sur l'activite des immigrantes. Toutefois, l'hypothese selon laquelle les niveaux d'activite feminine dans le pays d'origine traduisent les attitudes culturelles a l'egard des roles sexospecifiques n?a pas ete examinee en profondeur. En outre, on en sait peu sur la facon dont les caracteristiques du pays d'origine pourraient etre correlees avec les resultats des immigrantes apres leur entree sur le marche du travail dans le pays hote. Le present document etoffe la litterature specialisee existante en abordant trois questions : quelle est la relation entre les attitudes a l'egard des roles sexospecifiques dans le pays d'origine et l'activite feminine dans le pays d'origine? La relation entre le taux d'activite feminine dans le pays d'origine et l'activite des immigrantes dans le pays hote persiste-t-elle quand il est tenu compte de l'effet des attitudes a l'egard des roles sexospecifiques dans le pays d'origine? Le taux d'activite feminine dans le pays d'origine et les attitudes a l'egard des roles sexospecifiques dans le pays d'origine sont-ils associes aux salaires des immigrantes au Canada?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.432
GPT teacher head0.505
Teacher spread0.073 · 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 teacher head, not a consensus.

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDirection des études analytiques : documents de rechercheSame topicEducation, sociology, and vocational trainingFrench-language works237,207