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Record W7135474103

Development of educational systems Czech and Slovak Republic after the division of Czechoslovakia in 1993

2016· dissertation· cs· W7135474103 on OpenAlexaboutno aff
Lucie Francová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2016
Typedissertation
Languagecs
FieldSocial Sciences
TopicEducation, Psychology, and Social Research
Canadian institutionsnot available
Fundersnot available
KeywordsSlovakCzechWork (physics)LegislatureQuarter (Canadian coin)Comparative educationComparative researchPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

Thesis reviews the development of educational systems Czech and Slovak Republic after the division of Czechoslovakia in 1993. The common historical background in educational policy is the starting point for monitoring the development of these educational systems. The work aims to map and compare the development of educational systems of Czech and Slovak Republic. Describes historical events that have influenced their present form, and the issue is mapping of several aspects. Thesis is mapping these aspects in terms shaping the structure of educational systems, management and financing of education and educational policy. Also is mapping the important legislative steps and published educational documents. The comparative part thesis equates the education systems of both countries. It aims to find the answer how far apart to move away these two educational systems over the last quarter century and is describing the defining characteristics of the current differences. This comparison is carried for a period of ten years, and as a basis of this serves studies from 2004, 2009, 2014. KEYWORDS education system, education, Czech Republic, Slovak Republic, educational policy, development, comparation

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.007
Science and technology studies0.0020.004
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.342
Teacher spread0.325 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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