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Record W3127545355 · doi:10.31489/2020ped4/33-41

Good practices for family and school community: world and domestic experience

2020· article· en· W3127545355 on OpenAlexaboutno aff
B Vasic, M Utepov, V Kubieva

Bibliographic record

VenueBulletin of the Karaganda University Pedagogy series · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Political scienceEconomic growth

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.336
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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