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Record W2585926756 · doi:10.1080/15283488.2016.1268962

Community Involvement and Narrative Identity in Emerging and Young Adulthood: A Longitudinal Analysis

2017· article· en· W2585926756 on OpenAlexafffund
Julian Hasford, Kayleigh Abbott, Susan Alisat, S. Mark Pancer, Michael W. Pratt

Bibliographic record

VenueIdentity · 2017
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsWilfrid Laurier UniversityToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeMaturity (psychological)Identity (music)Longitudinal studyPsychologyNarrative identityDevelopmental psychologyEarly adulthoodSet (abstract data type)Perspective (graphical)Personal identityNarrative inquiryYoung adultSelf-conceptMedicine

Abstract

fetched live from OpenAlex

This study examines community engagement in youth and emerging adulthood from a narrative identity perspective, based on analyses of a longitudinal data set of 72 participants from ages 17 to 32. At ages 26 and 32, participants told narratives about a key community experience from their personal lives, which was rated for six dimensions. In addition, questionnaire measures of community involvement and general identity status development were administered at ages 17, 26, and 32. We found that patterns of community involvement at age 17 predicted levels of community involvement and qualities of community narratives at ages 26 and 32 and that community narratives were significantly correlated with concurrent measures of identity maturity and community involvement. Limitations and implications for future research are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.397
Teacher spread0.345 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2017
Admission routes2
Has abstractyes

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