Introduction to the special section on the study of social withdrawal during childhood and adolescence: In honor of Dr. Kenneth H. Rubin
Bibliographic record
Abstract
This special section is in honor of Dr. Kenneth H. Rubin and his unparalleled intellectual contribution to the study of the development and implications of social withdrawal. It also recognizes his almost 50 years of enthusiastic and devoted mentorship and international collaboration, which has stimulated numerous scholars around the world to investigate social withdrawal-related topics. The six contributions in this special section are written by scholars from diverse perspectives and backgrounds and include longitudinal datasets from four different countries. This introduction highlights the empirical contributions of these studies, characterized into three broad categories that have been central to Ken’s enormously influential work on social withdrawal: (1) peers as contributors to, and outcomes of, social withdrawal; (2) the consideration of the diverse contexts in which social withdrawal can occur; and (3) social withdrawal as a modifiable risk factor. Together, these studies extend knowledge about social withdrawal and its concomitants, set the stage for future research and intervention efforts, and honor the legacy of Dr. Kenneth H. Rubin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".