Distinguishing children who form new best-friendships from those who do not
Bibliographic record
Abstract
Three groups were identified using best-friendship nominations at two time points surrounding the transition to middle school (Time 1: Spring of 5th grade; Time 2: Fall of 6th grade): (i) children who had no best-friendship at Time 1, but had a best-friendship at Time 2 (best-friendship gain; N = 109); (ii) children who had no best-friendship at either Time 1 or 2 (chronically best-friendless; N = 105); and (iii) children with a best-friendship at both Times 1 and 2, but with different peers at each time (best-friendship change; N = 120). Peer nominations of social behaviors and victimization were collected at Times 1 and 2. Findings suggest that attraction to similar others, in addition to increased displays of prosocial behaviors, facilitate the formation of new best-friendships for both initially best-friendless and best-friended children.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".