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Record W2565416305 · doi:10.5539/jel.v6n2p53

Early Childhood Education Curricula: Human Rights and Citizenship in Early Childhood Education

2016· article· en· W2565416305 on OpenAlexvenueno aff
Μαρίνα Σούνογλου, Aikaterini Michalopoulou

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipHuman rightsObligationCurriculumContext (archaeology)PsychologyEarly childhood educationAffect (linguistics)SociologyPedagogyIntervention (counseling)Social psychologyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

This study examines the human rights and the notion of citizenship under the prism of pedagogical science. The methodology that was followed was the experimental method. In a sample of 100 children-experimental group and control group held an intervention program with deepening axes of human rights and the concept of citizenship. The analysis of the findings presented in four axes. The first relates to the analysis of the responses of the two groups using quantitative data. The second axis concerns the discourse analysis of children’s responses. The third axis relates to involve children and the fourth in the pop up program of children’s activities. In conclusion, according to the survey results, children may affect their participation shaping the curriculum at micro level but also affect their behavior in the macro. Children seem to understand a pedagogical context the concept of human rights and the concept of citizenship in their ability to influence the school and not only the daily life, respect the wishes of others, to understand the limits and restrictions in school and local community, their participation as a social obligation but also a right, to the understanding of human rights and children’s rights as a premise for the quality of their lives.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.028
GPT teacher head0.341
Teacher spread0.313 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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