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Record W2049237415 · doi:10.5539/ies.v6n12p1

Role of Social Studies for Pre-Service Teachers in Citizenship Education

2013· article· en· W2049237415 on OpenAlexvenueno aff
Seyedali Ahrari, Jamilah Othman, Md. Salleh Hassan, Bahaman Abu Samah, Jeffrey Lawrence D’Silva

Bibliographic record

VenueInternational Education Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsSocial studiesCivicsCitizenship educationCitizenshipPedagogyCivic engagementHumanismActive citizenshipSociologyDemocracySocial changePublic relationsMathematics educationPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Developing pre-service teachers civically is the oldest need which is known for social studies. Social studies are the most humanistic science between other sciences. It is due to the goal of social studies to focus more on civic issues and its content. Teacher students can gain skill, knowledge, and trait of being a good citizen through courses and curricular activities by attending in social studies classrooms. Based on the importance of schools to cultivate civic values, this paper concentrates on prospect teachers as agents of social change for new generation. The civic function of social studies is based on the unique technique brought by them for teaching in classrooms. It is hoped that it may compel educational policymakers to develop future teachers to transmit civic knowledge and values for a democratic society and better responsible citizenship.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.014
Scholarly communication0.0130.006
Open science0.0010.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0140.001

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 head0.194
GPT teacher head0.507
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations12
Published2013
Admission routes1
Has abstractyes

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