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Record W4386040453 · doi:10.5772/intechopen.111025

The Social Contexts of Young People - Engaging Youth and Young Adults

2023· book· en· W4386040453 on OpenAlexaboutno aff

Bibliographic record

VenueEducation and human development · 2023
Typebook
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersPurdue UniversityBill and Melinda Gates Foundation
KeywordsPsychologyDevelopmental psychologySociology

Abstract

fetched live from OpenAlex

This edited volume investigates young people within their social contexts. The focus is on engaging young people as they transition from youth into young adulthood. Key advantages of this book are its embodiment of interdisciplinarity in gathering research across a range of diverse methods, theories, settings, and countries. The volume begins with reviews of key theories and methods in understanding young people within their social networked contexts of generosity, networks, identity, and ethnic heritage. The second section includes chapters attending to education and work as contexts for transitions to adulthood, counseling, meaning, and aesthetics from high school to college and into workplaces. The third section includes chapters studying community engagement and the well-being of young people, including social support, meaning in life, religiosity, spirituality, stress coping, yoga, and sports. The diverse topics addressed in this edited volume are generosity, philanthropy, voluntary action, social networks, social identity, personhood, ethnic heritage, post-colonialism, intersectionality, personality, lived experiences, informal economy, sustainability, pandemic, family support, educational counselors, motivation, ?Not in Education, Employment, or Training? (NEET), everyday aesthetics, built environment, generativity, community, adult allies, youth engagement, life satisfaction, spiritual identity, religious affiliation, stress, practicing yoga, sexual violence, athletes, sports climate, pressures to perform, resilience, and neurodiversity. Disciplines span economics, business, education, sociology, psychology, medical science, geography, journalism, architecture, engineering, science and technology, and applied sciences. Methods include quantitative surveys, qualitative in-depth interviews, life course biographies, ethnographic case studies, bibliometric analysis, and integrative reviews. Young people are investigated across thirteen countries, including the United States, United Kingdom, Yemen, Ghana, Bahrain, Norway, Denmark, Finland, Sweden, Iceland, Canada, Romania, and the Netherlands.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.344
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.317
Teacher spread0.290 · 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 designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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