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Record W4205625897 · doi:10.5944/reec.40.2022.31442

National Reports and Global Education Policy Diffusion

2021· article· en· W4205625897 on OpenAlexaboutno aff
Daniel Capistrano, Christyne Carvalho

Bibliographic record

VenueRevista Española de Educación Comparada · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHomogeneousComparative educationInterpretation (philosophy)Similarity (geometry)Comparative researchRegional scienceRelevance (law)Diversity (politics)International educationConceptual frameworkHigher educationEconomic growthGeographySociologySocial scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Comparative research projects have become one of the main sources of information to investigate national systems of education and to inform education policy making at the national level. However, the way that national education authorities interpret and use the results of these projects may differ substantially among countries. This process, that we refer to as the national interpretation in comparative education, is overlooked in the debate regarding comparative research projects in education. This paper addresses this issue analysing national reports of the OECD Teaching and Learning International Survey (TALIS) from eight different countries: Australia, Brazil, Canada (Alberta), Chile, England, Mexico, Portugal and Spain. The results indicate that the national interpretation and reporting of international comparative data is fairly homogeneous considering the socio-educational diversity of the selected countries. However, our analysis also suggests that reports from English-speaking countries (Australia, Canada, and England) have a higher degree of similarity with the survey’s conceptual framework, whereas national reports from Mexico and Chile showed a lower degree of similarity. Moreover, our analysis reinforces the relevance of understanding countries’ focus and interpretation of evidence produced by international comparative research projects in education.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.360
Teacher spread0.346 · 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 designTheoretical or conceptual
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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevista Española de Educación ComparadaSame topicGlobal Educational Policies and ReformsFrench-language works237,207