Good practices for family and school community: world and domestic experience
Bibliographic record
Abstract
The article is devoted to the study of theoretical and practical issues on effective strategies of double capacity building for family and school unification in the Republic of Kazakhstan. In this regard, the world practices of effective strategies for uniting family and school were studied. Among foreign studies, it is necessary to distinguish such forms of education with a greater share of parental participation as homeschooling. In the United States (3 % of all school children, about 1.5 million people), Canada, and the United Kingdom. In Russia — from 70 to 100 thousand children. In Kazakhstan offer various forms from absolute «loosening» and «unschooling» («unschooling») to distance learning, including in online schools, and external exams, for example, via Skype. American Association Boston Basic: partners and advisors operate mainly on charitable donations from the public and the government. The primary role of the Association is to educate black par-ents in raising children from birth. The U.S. Department of Education and Science's Early Childhood Longi-tudinal Study Program (ECLS) includes four longitudinal studies that examine child development, school readiness, and early school experience. In domestic practice, the Private Fund «Just Support» (Almaty, Ka-zakhstan) should be highlighted. The Fund works with 30 educational organizations of Almaty city and 30 organizations of East Kazakhstan region. The Fund's mission is to contribute to the development of the Re-public of Kazakhstan's human capital.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.023 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".