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Record W4309619921 · doi:10.1177/00221678221132331

Humanistic Optimal Functioning Predicts Low Youth Violence

2022· article· en· W4309619921 on OpenAlexafffund
Roger G. Tweed, Gira Bhatt, Stephen Dooley, Jodi L. Viljoen, Kevin S. Douglas, Nathalie Gagnon

Bibliographic record

VenueJournal of Humanistic Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsSimon Fraser UniversityKwantlen Polytechnic University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGratitudeAggressionPsychologyForgivenessHumanismClinical psychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

This study assessed whether indicators of humanistic optimal functioning were predictive of lower levels of violence among youth across a 6-month period. Youth ( N = 346) aged 12 to 14 years completed measures of authenticity and of positive regard for others (generalized trust, forgiveness, and gratitude). Approximately 6 months later, the youth reported violence, criminal offenses, and indicators of potential violence, and for some ( n = 266), a teacher provided ratings of aggression. Authentic living, some elements of generalized trust, forgiveness, and gratitude predicted lower levels on indicators of aggression or violence or readiness for violence 6 months later. The relation between humanistic predictors and violence-related outcomes was larger for youth at elevated risk for violence. Unexpectedly, a subtype of authenticity, “resisting external influence,” predicted higher violence, but other outcomes were in the expected direction. Thus, a humanistic lens may have value in examinations of societal violence.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.993

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.042
GPT teacher head0.383
Teacher spread0.341 · 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 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

Citations0
Published2022
Admission routes2
Has abstractyes

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