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Record W3168474594

Avoiding and withdrawing from the peer group.

2018· article· en· W3168474594 on OpenAlexaff
Kenneth H. Rubin, Julie C. Bowker, Matthew G. Barstead, Robert J. Coplan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsCarleton University
Fundersnot available
KeywordsGroup (periodic table)Computer sciencePsychologyChemistry
DOInot available

Abstract

fetched live from OpenAlex

Avoiding and Withdrawing from the Peer Group In many ways this chapter concerns a topic unlike most that appear in this Handbook. Rather than focusing on the ways in which children and adolescents may interact with their peers, this chapter is centered on those children who, for whatever reason, engage rarely in peer interaction. As noted throughout this Handbook, children who are socially engaging and competent interact with peers in ways that allow the establishment and maintenance of positive relationships. Such children fare well in their social and academic lives. Alternatively, their socially unskilled counterparts often suffer from peer rejection, friendlessness, and loneliness; furthermore, they are thought to be at risk for a wide range of socioemotional and academic difficulties. In this chapter, we focus on children who avoid and rarely interact with their peers and who suffer deeply for their withdrawal. HISTORICAL BACKGROUND For at least two decades, researchers have argued that children who do not have adequate or “typical ” peer interactions and peer relationship experiences may be at risk for later maladjustment. Such a conclusion has been reinforced by studies demonstrating that peer rejection in childhood predicts psychopathology and school drop-out, among other negative consequences in adolescence

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.994

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 science0.0000.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.351
Teacher spread0.289 · 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 designQualitative
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

Citations17
Published2018
Admission routes1
Has abstractyes

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