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Record W4380876342 · doi:10.5744/bi.2023.0006

Emerging Adolescence

2023· article· en· W4380876342 on OpenAlexaff
Lauren Avery, Mary Lewis

Bibliographic record

VenueBioarchaeology International · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBioarchaeologySituatedPeriod (music)Developmental psychologyPsychologyAdolescent developmentGender studiesSociologyAnthropologyAesthetics

Abstract

fetched live from OpenAlex

Adolescence is marked by a wide range of biological, social, and neurological changes. Adolescents are stereotypically viewed as reckless, impulsive, and troubled, but research across the social and biomedical sciences is demonstrating that this is a narrow view of a dynamic period of life. Now, research is showing that adolescents are frequently responsible for the creation and transmission of new ideas and practices and for the creation of new social bonds, which can contribute to personal and community growth. In short, adolescents are key to the development and success of a community. The bioarchaeological study of adolescence not only speaks to the experiences of adolescents but also captures the life of a community, especially as this period encapsulates early life experiences and lays the foundations for later adult health outcomes. Consequently, the study of adolescence in past populations provides deep-time insights into adolescence as a uniquely human experience. This special issue of Bioarchaeology International focuses on newly developing work within the bioarchaeological study of adolescence, demonstrating how researchers can use bioculturally informed research to advance our understanding of adolescence in the past. In doing so, we demonstrate where the study of adolescence has come from, where it is presently situated, and where we may take it moving forward, as the study of adolescence not only emerges but also flourishes.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.999

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 studies0.0000.040
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.032
GPT teacher head0.289
Teacher spread0.256 · 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
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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

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