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Future Directions in Youth Involvement Research

2009· article· en· W2061463414 on OpenAlexaff
Linda Rose‐Krasnor

Bibliographic record

VenueSocial Development · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyDevelopmental psychologyPositive Youth DevelopmentProcess (computing)Social psychology

Abstract

fetched live from OpenAlex

Abstract Youth activity involvement has received increasing research and theoretical attention and should be of particular interest to social development investigators. Involvement has been correlated with a wide range of positive developmental indices, although not for all activities nor for all children. However, our ability to interpret such findings has been restricted by measurement and design limitations. Greater attention needs to be given to assessment issues and to determining the unique effects of psychological vs. behavioral engagement, as well as to capturing the dynamic nature of engagement and the moderating role of individual differences. ‘Big picture’ models of the entire engagement process (such as the one presented here) will help identify gaps in our research knowledge and will integrate existing evidence and theory.

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)0.075
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.007
Science and technology studies0.0030.008
Scholarly communication0.0100.025
Open science0.0070.008
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0300.002

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 head0.112
GPT teacher head0.385
Teacher spread0.273 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations93
Published2009
Admission routes1
Has abstractyes

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