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Record W4406873293 · doi:10.1111/ejed.70010

Towards an Ideal Model of Education for Critical Citizenship. An Analysis of the Spanish Curricular Change in Social Sciences

2025· article· en· W4406873293 on OpenAlexaff
Elisa Navarro‐Medina, E. Wayne Ross, Noelia Pérez‐Rodríguez, Nicolás de-Alba-Fernández

Bibliographic record

VenueEuropean Journal of Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of British Columbia
FundersUniversidad de Sevilla
KeywordsCitizenshipIdeal (ethics)Citizenship educationSociologyPedagogyCritical theorySocial changePolitical scienceMathematics educationSocial sciencePsychologyLaw

Abstract

fetched live from OpenAlex

ABSTRACT In this study, we analysed the presence of citizenship education in the new Spanish social sciences curriculum, focusing on both the primary and secondary education stages. The relevance of the study stems from the need to adapt to a new reality, in which it is crucial to develop in children and young people the skills to understand, interpret and make critical decisions. Considering the model outlined as ideal, and being aware of the difficulty involved in achieving it, we took as a reference a possible model to analyse the Spanish curriculum, the ICCS study framework. The research presented is based on a review of policy documents and analyses the curricula of compulsory education stages through a content analysis technique. The results show that in the Spanish curriculum, under the logic of the ICCS framework, cognitive skills and citizen content are more prevalent than those based on attitudes and engagement. This issue prompts us to reflect on the future changes that should be made to approach the model we consider relevant.

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)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0020.013
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.103
GPT teacher head0.445
Teacher spread0.342 · 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 designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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