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A review of neighborhood effects and early child development: How, where, and for whom, do neighborhoods matter?

2017· review· en· W2616058623 on OpenAlexaff
Anita Minh, Nazeem Muhajarine, Magdalena Janus, Marni Brownell, Martin Guhn

Bibliographic record

VenueHealth & Place · 2017
Typereview
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of ManitobaLearning PartnershipManitoba HealthMcMaster UniversitySaskatchewan HealthUniversity of Saskatchewan
Fundersnot available
KeywordsGeographyPsychologySociology

Abstract

fetched live from OpenAlex

This paper describes a scoping review of 42 studies of neighborhood effects on developmental health for children ages 0-6, published between 2009 and 2014. It focuses on three themes: (1) theoretical mechanisms that drive early childhood development, i.e. how neighborhoods matter for early childhood development; (2) dependence of such mechanisms on place-based characteristics i.e. where neighborhood effects occur; (3) dependence of such mechanisms on child characteristics, i.e. for whom is development most affected. Given that ecological systems theories postulate diverse mechanisms via which neighborhood characteristics affect early child development, we specifically examine evidence on mediation and/or moderation effects. We conclude by discussing future challenges, and proposing recommendations for analyses that utilize ecological longitudinal population-based databases.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.408
Teacher spread0.328 · 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

Citations353
Published2017
Admission routes1
Has abstractyes

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