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How Experience Gets Under the Skin to Create Gradients in Developmental Health

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.944
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.138
GPT teacher head0.447
Teacher spread
0.309 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Social environments and experiences get under the skin early in life in ways that affect the course of human development. Because most factors associated with early child development are a function of socio-economic status, differences in early child development form a socio-economic gradient. We are now learning how, when, and by what means early experiences influence key biological systems over the long term to produce gradients: a process known as biological embedding. Opportunities for biological embedding are tethered closely to sensitive periods in the development of neural circuitry. Epigenetic regulation is the best example of operating principles relevant to biological embedding. We are now in a position to ask how early childhood environments work together with genetic variation and epigenetic regulation to generate socially partitioned developmental trajectories with impact on health across the life course.

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.

The record

Venue
Annual Review of Public Health
Topic
Early Childhood Education and Development
Field
Social Sciences
Canadian institutions
Sunny Hill Health Centre for ChildrenLearning PartnershipUniversity of British Columbia
Funders
not available
Keywords
Life course approachEarly childhoodChild developmentEpigeneticsDevelopmental psychologyEmbeddingFunction (biology)PsychologyEpigenesisBiologyComputer scienceEvolutionary biologyArtificial intelligenceGeneticsDNA methylation
Has abstract in OpenAlex
yes