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Record W4404332810 · doi:10.1111/cdev.14192

Determinants of socioemotional and behavioral well-being among First Nations children living off-reserve in Canada: A cross-sectional study

2024· article· en· W4404332810 on OpenAlexaffabout
Sawayra Owais, Maria B. Ospina, C. Lawrence Ford, Troy Hill, John T.P. Lai, John E Krzeczkowski, Jacob A. Burack, Ryan J. Van Lieshout

Bibliographic record

VenueChild Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsBrock UniversityWestern UniversityMcGill UniversityQueen's UniversityMcMaster University
Fundersnot available
KeywordsSocioemotional selectivity theoryIndigenousPsychologyWell-beingDevelopmental psychologyCross-sectional studyCross-culturalGerontologyMedicineEcologySociology

Abstract

fetched live from OpenAlex

Few studies have focused on off-reserve Indigenous children and families. This nationally representative, cross-sectional study (data collected from 2006 to 2007) examined Indigenous- and non-Indigenous-specific determinants associated with positive socioemotional and behavioral well-being among First Nations children living off-reserve in Canada. The parents or other caregivers of 2990 two-to-five-year-old children (M = 3.65; 50.6% male) reported on their children's socioemotional and behavioral well-being and a range of child, parent, and housing characteristics. Being taught an Indigenous culture, greater community cohesion, caregiver nurturance, good parental/other caregiver health, and fewer household members were associated with better socioemotional and behavioral well-being. These results highlight the importance of leveraging Indigenous-specific determinants and acknowledging non-Indigenous-specific factors, to promote the well-being of First Nations children living off-reserve.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.310
Teacher spread0.295 · 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 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

Citations5
Published2024
Admission routes2
Has abstractyes

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