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Record W2566030629 · doi:10.1080/10609393.2015.1068567

The Difference That One Year of Schooling Makes for Russian Schoolchildren

2015· article· en· W2566030629 on OpenAlexaboutno aff
Yu. A. Tiumeneva, Ju. V. Kuzmina

Bibliographic record

VenueRussian Education & Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationSocioeconomic statusCzechPsychologyRegression discontinuity designDeveloped countryDemographic economicsMathematics educationEconomic growthDemographySociologyPopulationPedagogyEconomicsMathematicsStatistics

Abstract

fetched live from OpenAlex

The PISA 2009 data (in reading) investigated the effectiveness of one year of schooling in seven countries: Russia, Czech Republic, Hungary, Slovakia, Germany, Canada, and Brazil. We used an instrumental variable, which allowed us to estimate the effect of one year of schooling through the fuzzy method of regression discontinuity. The analysis was performed both for regular and vocational education programs collectively as well as individually for regular schools. It was found that in general for Russian students enrolled in all programs, the effectiveness of one year of schooling is insignificant. In countries that practice the early separation of students into regular and vocational programs, the effectiveness of schooling is lower than in countries where all fifteen-year-olds are enrolled in regular programs. The effectiveness of one year of schooling for students enrolled in regular educational programs is significant in all countries. Students enrolled in vocational programs typically perform more poorly than those enrolled in regular programs. The strength of the relationship between the socioeconomic status of the student's family and the effectiveness of schooling are highly dependent on the education system and vary from country to country. For Russia, as well as for some other countries, the effectiveness of schooling does not depend on socioeconomic status. The significance of these results for the evaluation of the effectiveness of schooling, and in particular for the fair evaluation of national achievement in countries that offer different educational trajectories, is discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.058
GPT teacher head0.339
Teacher spread0.281 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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