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Record W4404623668 · doi:10.1016/j.bandc.2024.106242

Ear to the ground! socioeconomic status, environmental stress, and the neural substrate of selective attention

2024· article· en· W4404623668 on OpenAlexafffund
Amedeo D’Angiulli, Shanine Kamgang, Rachelle Humes, Keren Ighalo, Renee Baysarowich

Bibliographic record

VenueBrain and Cognition · 2024
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsChildren's Hospital of Eastern OntarioWilfrid Laurier UniversityCarleton University
FundersCHEO Research Institute
KeywordsSocioeconomic statusPsychologyNeural substrateSubstrate (aquarium)Stress (linguistics)Environmental stressDevelopmental psychologyCognitionCognitive psychologyNeuroscienceEnvironmental healthEcologyLinguisticsGeographyEnvironmental protectionPopulation

Abstract

fetched live from OpenAlex

We reanalyzed data originally published by Berman and Friedman (1995), who recorded event related potentials (ERPs) while children and adults with low, medium, and high socioeconomic status (SES) detected oddball auditory targets (tones and consonant-vowel sequences) among distractors. The ERP differential measuring how much attention was allocated to the targets vs. distractors increased significantly with SES, independently of age. To explain these findings, we integrate the ear to the ground hypothesis and the socioenvironmental epigenetic stress approach. According to the ear to the ground hypothesis, frequent and prolonged environmental uncertainty and hazard induce low-SES children to learn adaptive over-vigilance, attending disproportionately to stimuli that are currently irrelevant but may quickly become relevant and thus require an immediate survival response. Socioenvironmental epigenetic stress refers to the bidirectional interaction between a stress-inducing environment and the impact and expression of transgenerational gene selections in low-SES contexts. Because low-SES individuals are historically under and misrepresented in research, the proposed framework contributes to increase our understanding of how socioeconomic and environmental conditions may affect neurocognitive development. This offers significant points of entry for future interventions and policies targeting macrosocial settings (i.e., education and the justice system) and microsocial ontogenetic settings (i.e., individuals and families).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.304
Teacher spread0.291 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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