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Record W1574925695 · doi:10.14507/epaa.v21n48.2013

More than a new country: Effects of immigration, home language, and school mobility on elementary students’ academic achievement over time

2013· article· en· W1574925695 on OpenAlexaboutno aff
Orlena Broomes

Bibliographic record

VenueEducation Policy Analysis Archives · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationReading (process)Mathematics educationHome languageAcademic achievementPsychologyLogistic regressionDevelopmental psychologyMedicineGeographyPolitical science

Abstract

fetched live from OpenAlex

This study investigated the effects of immigration and home language on academic achievement over time. Using data from Ontario’s Assessments of Reading, Writing and Mathematics administered to the same students in Grades 3 and 6, logistic regression was used to predict if students achieved proficiency in Grade 6 if they were not proficient in Grade 3. The results indicate that home language or interactions with home language are significant in most cases. In addition, students who speak a language other than or in addition to English at home are, in general, a little more likely to be proficient at Grade 6. Most students who were born outside of Canada were significantly more likely than students born in Canada to stay or become proficient in Reading, Writing, and Mathematics by Grade 6. These results highlight the importance of considering the enormous heterogeneity of immigrants’ experiences when studying the effects of immigration on academic performance and the dire limitations of datasets that do not collect such data.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.286
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.347
Teacher spread0.342 · 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.

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

Citations2
Published2013
Admission routes1
Has abstractyes

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