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State Policy in the Field of Education: Legal Origins and Development

2021· article· en· W7140208469 on OpenAlexaboutno aff

Bibliographic record

VenueRU SCIENCE · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionalisationCLARITYNormativeConsolidation (business)State (computer science)Field (mathematics)ConstitutionalismCoherence (philosophical gambling strategy)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

The abstract presents the results of a historical-legal analysis of state policy in the field of education in the Russian state from the 10th to the 18th centuries. It demonstrates that, at early stages, educational practices developed primarily within ecclesiastical institutions and local forms of instruction in the absence of a distinct body of educational legislation. The study shows that the normative institutionalization of certain educational elements became visible in the sixteenth century and reflected a predominantly church-oriented model of educational governance. It further establishes that the late seventeenth and the first quarter of the eighteenth centuries marked an institutional shift characterized by the expansion of specialized schools and the strengthening of the state’s role in organizing education, including elements of compulsory attendance and secularization. The analysis also identifies that, in the second half of the eighteenth century, prerequisites for the systematization of the school network and for socially oriented measures emerged, indicating the consolidation of education as a sphere of public policy. The article concludes that the sustainability of educational transformations depended on the coherence of regulatory sources, the clarity of the allocation of competences, and the predictability of law enforcement.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.014
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.442
Teacher spread0.396 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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