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Record W2768255470 · doi:10.1007/978-3-319-47143-3_4

Early Childhood Health and the Life Course: The State of the Science and Proposed Research Priorities

2017· book-chapter· en· W2768255470 on OpenAlexaff
W. Thomas Boyce, Clyde Hertzman

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsLearning PartnershipUniversity of British Columbia
FundersUniversity of CambridgeAmerican Society of NephrologyU.S. Department of Health and Human Services
KeywordsLife course approachMental healthThrivingDevelopmental psychologyVulnerability (computing)PsychologyPovertyDisadvantagePsychological interventionEarly childhoodPsychopathologyUnderpinningDevelopmental psychopathologyClinical psychologyPsychiatryPolitical sciencePsychotherapist

Abstract

fetched live from OpenAlex

Abstract This chapter begins with an assertion that, beyond the cultural traditions that affirm childhood as a period of special and lasting importance, a new science of child development reveals an influence of the early years throughout the life course. Through processes of “biological embedding,” early developmental experiences and exposures become neurobiologically instantiated in the brain and genome, thereby affecting trajectories of health and development for the remainder of life. The socioeconomic maldistribution of exposures to adversities and misfortune allots a disproportionate share of physical and mental morbidities to those growing up in conditions of poverty and disadvantage. These outcomes now appear related to epigenetic interactions between aspects of allelic variation-based vulnerability and the assaultive or supportive conditions of early life. Future research should thus address how epigenetic regulation of gene expression is linked to the neurobiological processes underpinning developmental psychopathology and other maladaptive outcomes. Richer understanding of how early environments can amplify or diminish the impacts of adversity exposure will provide new insights to guide the construction of novel, effective, and early interventions.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.008
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.363
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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations29
Published2017
Admission routes1
Has abstractyes

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