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Record W4319791111 · doi:10.1111/chso.12688

The assessment of cliques in bound child and adolescent groups: A systematic scoping review

2023· article· en· W4319791111 on OpenAlexaff
Madison Robertson, Jordan Sutcliffe, Cailie S. McGuire, Mark W. Bruner, Jean Côté, Luc J. Martin

Bibliographic record

VenueChildren & Society · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsNipissing UniversityQueen's University
Fundersnot available
KeywordsAntecedent (behavioral psychology)PsychologySocial network analysisDevelopmental psychologyComputer scienceSocial mediaWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract The purpose of this systematic scoping review was to examine research that has assessed cliques within bound child and adolescent groups. A total of 10,878 studies were obtained from six research databases, with 68 studies ultimately being included. Results highlighted a range of methods used for the assessment of cliques with social network analysis and peer nominations being most prevalent. Moreover, research question(s) were encompassed within the following categories: antecedent‐oriented (n = 13), outcome‐oriented (n = 43) or the general nature of cliques (n = 12). These findings demonstrate the complexity of cliques and the need for nuanced approaches to exploring their implications for youth.

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)0.047
metaresearch head score (Gemma)0.166
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.166
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0260.020
Science and technology studies0.0020.003
Scholarly communication0.0070.006
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.347
Teacher spread0.323 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes1
Has abstractyes

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