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Record W2795642231 · doi:10.7758/rsf.2018.4.4.01

The Biosocial Approach to Human Development, Behavior, and Health Across the Life Course

2018· article· en· W2795642231 on OpenAlex
Kathleen Mullan Harris, Thomas W. McDade

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRSF The Russell Sage Foundation Journal of the Social Sciences · 2018
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsCanadian Institute for Advanced Research
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsBiosocial theoryLife course approachSocioeconomic statusPsychologySociologyDevelopmental psychologySocial psychologyDemographyPersonality

Abstract

fetched live from OpenAlex

Social and biological phenomena are widely recognized as determinants of human development, health, and socioeconomic attainments across the life course, but our understanding of the underlying pathways and processes remains limited. To address this gap, we define the "biosocial approach" as one that conceptualizes the biological and social as mutually constituting, and that draws on models and methods from the biomedical and social/behavioral sciences. By bringing biology into the social sciences, we can illuminate mechanisms through which socioeconomic, psychosocial, and other contextual factors shape human development and health. Human biology is a social biology, and biological measures can therefore identify aspects of social contexts that are harmful, as well as beneficial, with respect to well-being. By bringing social science concepts and study designs to biology and biomedicine, we encourage an epistemological shift that foregrounds social/contextual factors as important determinants of human biology and health. The biosocial approach also underscores the importance of the life course, as assessments of both biological and social features throughout human development over time, and across generations, are needed to achieve a full understanding of social and physical well-being. We conclude with a brief review of the papers in the volume, which showcase the value of a biosocial approach to understanding the pathways linking social stratification, biology, and 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.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0140.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.087
GPT teacher head0.415
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