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Record W2585403045 · doi:10.1080/13670050.2017.1281216

Speaking an Aboriginal language and school outcomes for Canadian First Nations children living off reserve

2017· article· en· W2585403045 on OpenAlexafffundabout
Anne Guèvremont, Dafna Kohen

Bibliographic record

VenueInternational Journal of Bilingual Education and Bilingualism · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsStatistics Canada
FundersIndigenous and Northern Affairs Canada
KeywordsPsychologyDemographyGeographySociology

Abstract

fetched live from OpenAlex

The importance of learning an Aboriginal language has been documented, yet associations with positive educational outcomes are inconclusive. Previous research in the area has been limited by small sample studies, lack of comparison groups, and the omission of the consideration of socio-demographic factors and cultural activity participation. This study uses the Canadian population-based Aboriginal Peoples Survey 2006 to examine the relationship between speaking an Aboriginal language, learning it in school, and educational outcomes for First Nations children living off reserve. Compared to children who did not speak an Aboriginal language, children who spoke an Aboriginal language and had school teachers help them learn the language at school were more likely to be rated as doing very well at school and had higher parent ratings of the importance of a post-secondary education, with no difference in the likelihood of being the appropriate age for grade, even after controlling for socio-demographic factors and participation in other cultural activities. These results suggest that learning an Aboriginal language in school is associated with positive outcomes for children who speak an Aboriginal language. Future research on this topic is needed including longitudinal studies and inclusion of direct measures of educational outcomes.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.404
Teacher spread0.387 · 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 designQualitative
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

Citations7
Published2017
Admission routes3
Has abstractyes

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Same venueInternational Journal of Bilingual Education and BilingualismSame topicIndigenous Health, Education, and RightsFrench-language works237,207