Adult Education and Learning Policy in the Czech Republic
Bibliographic record
Abstract
The Czech Republic was founded in 1993 as one of the successor countries following the break-up of Czechoslovakia. Czech society underwent a rapid transition to democracy and capitalism, with its social transformation being shaped predominantly by economic technocrats. Domains such as education and culture became marginalized in both social debate and government policy, and were largely left to market forces (Vymazal, 2002). Profound changes affected adult education’s legal framework, funding, stakeholders and practices. Formerly existing as a centrally governed system with a top-down hierarchy, adult education found itself in a situation of insufficient management and chaos. Its system fell apart, its elements partly destroyed and partly reoriented towards commercial activities, and subsequent policy change became driven by international organizations. This chapter reviews the recent two decades of policy reforms in the Czech Republic. It describes changes in the evolution of practices and in adult education terminology, paying special attention to (1) legislative amendments and division of responsibilities; (2) Europeanization and globalization of education policy; (3) statistical trends in adult participation in educational activities; and (4) the range of institutions involved in adult education. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".