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Record W3193760793 · doi:10.1002/ajcp.12551

Trajectories of Youth's Helping From Adolescence into Adulthood: The Importance of Social Relations and Values

2021· article· en· W3193760793 on OpenAlexafffundabout
Heather L. Ramey, Heather L. Lawford, S. Mark Pancer, M. Kyle Matsuba, Michael W. Pratt

Bibliographic record

VenueAmerican Journal of Community Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsKwantlen Polytechnic UniversityWilfrid Laurier UniversityBishop's UniversityOntario Centre of Excellence for Child and Youth Mental HealthStudents CommissionBrock UniversityHumber Polytechnic
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsProsocial behaviorPsychologyHelping behaviorTimelineSocial psychologySalience (neuroscience)Developmental psychologyPositive Youth DevelopmentHealth psychologyMoral developmentAmbivalencePublic health

Abstract

fetched live from OpenAlex

Helping behaviors (e.g., helping a sick friend, volunteering) are important forms of community involvement and likely change with age and life context. Yet, trajectories of community helping from adolescence through early adulthood have rarely been examined. It is also unclear how the roles of family, friends, and social attitudes might foster the development of helping behaviors across these years. We report on a study of community helping in a Canadian youth sample, across five intervals over a 15-year span, beginning at age 17 (N = 416). Helping displayed a quadratic trend, decreasing into the mid-20s, and then rebounding somewhat by 32. Social responsibility and salience of friends' prosocial moral values positively predicted age 17 community helping, whereas parents' moral values predicted less decrease in helping over this timeline. These findings add to an understanding of moral influences and social responsibility, in the potential shaping of youths' community helping behaviors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.380

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.328
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2021
Admission routes3
Has abstractyes

Explore more

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