BOSHLANG'ICH TA'LIMI TIZIMIDA BOLALARNING EMOTSIONAL-INTELLEKTUAL RIVOJLANTIRISHDA JAHON TAJRIBASI MODELLARI
Bibliographic record
Abstract
Annotatsiya. Ushbu maqolada boshlang‘ich ta’lim tizimida bolalarning emotsional-intellektual rivojlanish jarayonini jahon tajribasi asosida tahlil qilish masalalari yoritilgan. Maqolada AQSh, Finlyandiya, Yaponiya, Singapur va Kanada ta’lim tizimlarida qo‘llanilayotgan konseptual yondashuvlar qiyosiy o‘rganilib, CASEL modelining 5 asosiy kompetensiyasi – o‘zini anglash, o‘zini boshqarish, ijtimoiy ko‘nikmalar, empatiya va mas’uliyatli qaror qabul qilish – bolalar shaxsiy va ijtimoiy rivojida muhim omil ekanligi asoslab berilgan. Аннотация. В данной статье рассматриваются вопросы развития эмоционально-интеллектуальных способностей учащихся начальной школы на основе изучения мирового опыта. Проведён сравнительный анализ концептуальных подходов, применяемых в системах образования США, Финляндии, Японии, Сингапура и Канады. Особое внимание уделено модели CASEL, включающей пять ключевых компетенций: самопознание, саморегуляция, социальные навыки, эмпатия и ответственное принятие решений. Abstract. This article explores the development of emotional and intellectual abilities in primary education based on an analysis of international experience. A comparative study of conceptual approaches used in the education systems of the United States, Finland, Japan, Singapore, and Canada has been conducted. Special attention is given to the CASEL framework, which comprises five core competencies: self-awareness, self-management, social skills, empathy, and responsible decision-making.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.018 |
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".