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Record W2965740100 · doi:10.30786/jef.573614

A Study on Comparative Examination of the Theme "Power, Authority and Management" in the Social Studies Curriculums of Turkey, Canada (Alberta) and England

2019· article· en· W2965740100 on OpenAlexaboutno aff
Mustafa Yavuz, Tuğba Cevriye Özkaral

Bibliographic record

VenueJournal of Education and Future · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicValues and Moral Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumTheme (computing)CharterSocial studiesConstitutionPolitical scienceContent analysisQualitative researchSociologyLawPedagogySocial science

Abstract

fetched live from OpenAlex

This study aims to examine and compare the curricula of Social Studies courses in Turkey, Canada (Alberta) and England in terms of the theme "Power, Authority and Management". It is aimed to determine the similarities and the differences. In the study, qualitative research method was adopted. The source of the data consisted of the social studies curricula applied in Turkey, Canada (Alberta) and England. In the study, the criterion sampling of non-probability sampling methods was used. The findings of the study were obtained using a document analysis. In the analysis of data, descriptive analysis method of qualitative research techniques was used. In the light of the findings obtained in the study, it was seen that right, responsibility, freedom, democracy and constitution were common and were included in the programs of all three countries. It was also determined that the three countries included higher-order thinking skills related to the theme. Based on the research findings, documents such as the Canadian Charter of Rights and Freedoms and the La Grande Paix De Montréal Treaty that are being implemented in other countries may be included in the program in order to give students a universal perspective on laws and rules.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.991

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 studies0.0000.000
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 head0.042
GPT teacher head0.390
Teacher spread0.347 · 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 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
Published2019
Admission routes1
Has abstractyes

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