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Enregistrement W3008875173 · doi:10.23889/ijpds.v5i1.1147

Immigrant and ethnic neighbourhood concentration and reduced child developmental vulnerability

2020· article· en· W3008875173 sur OpenAlex
Daphne N. McRae, Nazeem Muhajarine, Magdalena Janus, Eric Duku, Marni Brownell, Barry Forer, Martin Guhn

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Notice bibliographique

RevueInternational Journal for Population Data Science · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueUrban, Neighborhood, and Segregation Studies
Établissements canadiensUniversity of British ColumbiaUniversity of ManitobaMcMaster UniversityUniversity of Saskatchewan
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésNeighbourhood (mathematics)Socioeconomic statusDemographyEthnic groupSocial vulnerabilityChild developmentPsychologyPopulationImmigrationDevelopmental psychologyGeographyPsychological interventionSociology

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Studies have consistently demonstrated a gradient between median neighbourhood income and child developmental outcomes. By investigating statistical outliers-neighbourhoods with children exhibiting less or more developmental vulnerability than that predicted by median neighbourhood income-there is an opportunity to identify other neighbourhood characteristics that may be enhancing or impeding early childhood development. OBJECTIVE: Testing a variety of neighbourhood factors, including immigrant or ethnic concentration and characteristics of structural disadvantage (proportion of social assistance recipients, homes in need of major repair, residents with high school education only, lone parent families, and residents moving in the last year) we sought to identify factors associated with more or less developmental vulnerability than that predicted by median neighbourhood income, for young children. METHODS: For this cross-sectional study we used validated Early Development Instrument (EDI) data (2003-2013) linked to demographic and socioeconomic Census and Tax Filer data for 98.3% of Canadian neighbourhoods (n=2,023). The purpose of the instrument is to report, at a population-level, children's school readiness. Children's developmental vulnerability was assessed in five domains (physical health and well-being, emotional maturity, social competence, language and cognitive development, and communication and general knowledge) in relation to the 10th percentile from a national normative sample. Levels of children's neighbourhood vulnerability were determined per domain, as percent of children vulnerable at a given domain. Neighbourhoods were grouped into three cohorts, those having lower than predicted, as predicted, or higher than predicted children's vulnerability according to neighbourhood median income. Using multivariable binary logistic regression we modelled the association between select neighbourhood characteristics and neighbourhoods with lower or higher than predicted vulnerability per domain, compared to neighbourhoods with predicted vulnerability. This allowed us to determine neighbourhood characteristics associated with better or worse child developmental outcomes, at a neighbourhood-level, than that predicted by income. RESULTS: In neighbourhoods with less child developmental vulnerability than that predicted by income, high or low immigrant concentration and ethnic homogeneity was associated with less vulnerability in physical (adjusted odds ratio (aOR) 1.66, 95% CI: 1.43, 1.94), social (aOR 1.30, 95% CI: 1.11, 1.51), and communication domains (aOR 1.24, 95% CI: 1.03, 1.47) compared to neighbourhoods with vulnerability concordant with income. Neighbourhood ethnic homogeneity was consistently associated with less developmental vulnerability than predicted by income across all developmental domains. Neighbourhood-level structural disadvantage was strongly associated with child developmental vulnerability beyond that predicted by median neighbourhood income. CONCLUSION: Canadian neighbourhoods demonstrating less child developmental vulnerability than that predicted by income have greater ethnic and ethnic-immigrant homogeneity than neighbourhoods with child developmental vulnerability concordant with income. Neighbourhood social cohesion and cultural identity may be contributing factors. Neighbourhood structural disadvantage is associated with poorer early childhood development, over and above that predicted by neighbourhood income. Neighbourhood-level policy and programming should address income and non-income related barriers to healthy child development.

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,508
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,000
Communication savante0,0000,002
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,121
Tête enseignante GPT0,400
Écart entre enseignants0,279 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle