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Record W2794219331

Global Citizenship Education in a Secondary Geography Course: The Students’ Perspectives

2014· article· en· W2794219331 on OpenAlexfundaboutno aff
Kyle D. Massey

Bibliographic record

VenueDergiPark (Istanbul University) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
FundersQueen's University
KeywordsCourse (navigation)CitizenshipMathematics educationPedagogySociologyGeographyPolitical sciencePsychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Global citizenship education is increasingly appreciated in Ontario, Canada, as an important componentof formal schooling. Although all disciplinary areas have a role to play in global citizenship education,geography provides an especially relevant context in which to foster the values and attitudes often citedas important for global citizenship. This study investigates how Grade 12 students, who had recentlycompleted the course “Canadian and World Issues: A Geographic Analysis”, conceive of the concept ofglobal citizenship, and experienced its values within this course. Qualitative data was collected throughinterviews with seven students. The interviews revealed four major themes relating to how the studentsconceptualized global citizenship: global awareness, belonging, caring, and commitment to action. Itrevealed students’ personal involvement with the concepts studied helped them learn to be globalcitizens, as did the rich discussions of global issues they experienced in class. Careful analysis of bothstudents’ conceptions of global citizenship and how they experienced global citizenship in thecurriculum exposed an uncritical perspective – one which emphasizes acts of charity and volunteerismrather than a commitment to social justice. The findings are valuable to teachers and teacher candidatesseeking to better engage their students in global issues and equip them with global thinking strategies,and to curriculum developers wishing to effectively incorporate values and topics concerning globalcitizenship within school curricula.

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)0.000
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 score0.746
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.009
GPT teacher head0.294
Teacher spread0.286 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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