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The Development of Young Children of Immigrants in Australia, Canada, the United Kingdom, and the United States

2012· review· en· W1926234128 on OpenAlexaffabout
Elizabeth Washbrook, Jane Waldfogel, Bruce Bradbury, Miles Corak, Ali A. Ghanghro

Bibliographic record

VenueChild Development · 2012
Typereview
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Ottawa
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEconomic and Social Research Council
KeywordsImmigrationDisadvantagedPsychologyDevelopmental psychologyCognitionVocabularyCognitive developmentEconomic growthPolitical scienceLinguistics

Abstract

fetched live from OpenAlex

In spite of important differences in some of the resources immigrant parents have to invest in their children, and in immigrant selection rules and settlement policies, there are significant similarities in the relative positions of 4- and 5-year-old children of immigrants in Australia, Canada, the United Kingdom, and the United States. Children of immigrants underperform their counterparts with native-born parents in vocabulary tests, particularly if a language other than the official language is spoken at home, but are not generally disadvantaged in nonverbal cognitive domains, nor are there notable behavioral differences. These findings suggest that the cross-country differences in cognitive outcomes during the teen years documented in the existing literature are much less evident during the early years.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.839
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.375
Teacher spread0.273 · 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
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

Citations95
Published2012
Admission routes2
Has abstractyes

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