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Race, Class, and Ethnicity in Young Adulthood

2015· other· en· W1505042481 on OpenAlexaboutno aff
Vonnie C. McLoyd, Kelly M. Purtell, Cecily R. Hardaway

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupDisadvantagedRace (biology)PsychologyDevelopmental psychologyPsychological resilienceLife course approachLife chancesSocial classIntersectionalityMental healthSocial capitalSocial psychologySociologyGender studiesPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract This chapter examines how social class, race, and ethnicity shape the transition to adulthood, drawing heavily on life course theory, developmental contextualism, and the concepts of risk, resilience, and social capital as analytic anchors. Four domains of functioning are discussed—conceptions of adulthood, mental health, paid employment, and educational attainment. Emphasis is given to studies that illuminate processes that link social location to the development of youth (mediational processes) and studies that examine sources of variation in developmental pathways among economically disadvantaged and ethnic minority youth, with special attention to the positive end of the risk dimension (i.e., promotive factors). We also highlight protective factors, that is, factors and processes that mitigate the negative effects of economic advantage and ethnic minority status on the functioning of youth during the transition to adulthood. Each major section of the chapter concludes with a summary and discussion of questions and issues that merit study in future research. The chapter emphasizes research based on U.S. samples, but incorporates research findings from youth in Canada and Western European countries.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.311
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.340
Teacher spread0.314 · 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.

Study designNot applicable
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

Citations8
Published2015
Admission routes1
Has abstractyes

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