Global Citizenship Education in a Secondary Geography Course: The Students’ Perspectives
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".