Psychosocial Predictors of Taiwanese Secondary Students' Self-Esteem
Bibliographic record
Abstract
This study investigated the relationships between psychosocial factors and self-esteem 1,672 Taiwanese senior high school students (779 boys, 893 girls). Students from Kaohsiung City, Taiwan, completed a Chinese version of the Secondary Student Questionnaire (SSQ), which measures self-esteem, depression, anxiety, stereotyped thinking, personality, and satisfaction with nonacademic performance at school. Students were categorized into four groups: (a) high academic achievement/low self-esteem (HALS); (b) high academic achievement/high self-esteem (HAHS); (c) low academic achievement/ low-self esteem (LALS); and (d) low academic achievement/high self-esteem (LAHS). Results showed that two variables, personality/satisfaction and anxiety, were predictive self-esteem for all four groups. Depression was predictive for all groups except low achievement and high self-esteem (LAHS). Research recommendations and educational implications are discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".