Bibliographic record
Abstract
This thesis examines the role of literary studies in critical global citizenship education (GCE) within a Canadian high school context. Grounded in recent educational literature, which argues for more critical approaches of GCE (Andreotti 2006; Andreotti et al. 2010; Marshall 2009; Pashby 2011; Pike 2008; Richardson 2008; Schultz 2007; Tallon 2012; Taylor 2011), I will explore how to implement critical GCE within the concrete lessons and practices of English literature classrooms. Drawing primarily on Stone-Mediatore’s literary theory of reading for enlarged thought, I will propose a new framework of reading for critical global citizenship through critical and reflexive engagement with marginalized narratives. A critique of curriculum materials for Craig Kielburger’s Free the Children and Robin Wiszowaty’s My Maasai Life, developed by Me to We and Free the Children, reveals how Western-oriented texts and safe, traditional reading practices contribute to a form of global citizenship that perpetuates Western hegemony and limits expressions of citizenship to benevolent actions. By contrast, by helping students engage critically and reflexively with marginalized experience narratives, educators may guide their students through a difficult and cyclical process, introduced by Andreotti and de Souza’s Through Other Eyes project (2008), of learning to unlearn, learning to listen, learning to learn, and learning to reach out. Through this process, students may begin to recognize their situatedness within mainstream frameworks that limit their abilities to consider alternative possibilities and futures. To demonstrate possibilities for implementing this fourfold reading process in the classroom, I will provide example reading activities for Chris Abani's novel, Song for Night, David Alexander Robertson and Madison Blackstone’s graphic novel, The Life of Helen Betty Osborne, and the documentary film, Dear Mandela.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.049 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".