Avoiding and withdrawing from the peer group.
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".