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Record W2992155326

COMPULSORY LEARNING ROMANIA IN EUROPEAN CONTEXT

2014· article· en· W2992155326 on OpenAlexaboutno aff
Pana Elena Cristina, Nisulescu Ileana

Bibliographic record

VenueRePEc: Research Papers in Economics · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)BusinessPolitical scienceEconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

Although in many respects, the EU imposes a unitary global policy (European Aquis) in compulsory education it gives freedom to the member countries in implementing their policies in national testing of pupils in monitoring schools and education systems. Currently national tests play a very important role in the development of educational policies, their results are analyzed in order to establish measures to reduce disparities between the levels of knowledge or improving vocational training of teachers. The results of these tests are used for many purposes including monitoring of standards, student progress from year to year, providing feedback to students and parents, guidance of teachers' work. However, normally there should be a direct and proportional connection between the results of the assessment and the budget given to each educational institution, the funding being the evaluation result. It should work as a stimulant in obtaining superior results. This link, although it seems to be implied, was difficult to be proved as long as the test results are not made public, nor is it confirmed by the implemented educational policies. Following comparisons made over time between Canada, the U.S. and EU countries it was found that the results of national tests in Europe are not used as a tool for empowerment, involving sanctions or rewards and subsequently to influence the allocation of resources.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.374
Teacher spread0.332 · 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.

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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