Self‐control, peer preference, and loneliness in Chinese children: A three‐year longitudinal study
Bibliographic record
Abstract
Abstract The purpose of this study was to explore the longitudinal links among Chinese children's self‐control, social experiences, and loneliness, largely from a developmental cascades perspective (which postulates mechanisms about how effects within a particular domain of functioning can impact across additional domains over time). Participants were N = 1,066 primary school students in Shanghai, P. R. China, who were followed over three years from Grade 3 to Grade 5. Measures of children's behavioral self‐control, peer preference, and loneliness were obtained each year from peer nominations and child self‐reports. Results indicated that as compared with the unidirectional and bidirectional models, the developmental cascade model represented the best fit for the data. Within this model, a number of significant direct and indirect pathways were identified among variables and over time. For example, self‐control was found to indirectly contribute to later decreases in loneliness via a pathway through peer preference. As well, peer preference both directly and indirectly contributed to later increases in self‐control. Finally, loneliness directly led to decreases in self‐control from Grade 3 to Grade 4, but not from Grade 4 to Grade 5. Results are discussed in terms of the implications of self‐control for Chinese children's social and emotional functioning over time.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".