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Record W1499755597

Tendances differentes en matiere de taux de citoyennete des immigrants au Canada et aux Etats-Unis

2011· preprint· fr· W1499755597 on OpenAlexaboutno aff
Feng Hou, Garnett Picot

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typepreprint
Languagefr
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Le present document examine les avantages sur le marche du travail associes au fait de devenir citoyen d'un pays hote, dans ce cas le Canada ou les Etats-Unis. Selon des recherches internationales recentes, il y aurait un avantage economique lie a l'obtention de la citoyennete. L'etude examine egalement l'ecart croissant entre les taux de citoyennete observes au Canada et aux Etats-Unis, ainsi que les differences en ce qui concerne les caracteristiques individuelles et celles de la region d'origine des immigrants, et ce, en vue d'expliquer les changements de l'ecart entre les taux de citoyennete entre les deux pays.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.034
GPT teacher head0.324
Teacher spread0.290 · 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 designObservational
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
Published2011
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in Economics→Same topicMigration and Labor Dynamics→French-language works237,207→