Navigating Place, Language and Culture in Canadian Education: Stories of Entangled Identities
Bibliographic record
Abstract
Abstract Humans possess the capacity to make sense of stories unfolding across different and difficult times with nuanced understanding and to unlearn and relearn what once seemed familiar. All human beings are storytellers, and the narratives of minorities deserve recognition and value within Westernised contexts. Drawing on sociocultural perspectives and employing a narrative inquiry approach, I share stories from my lived experiences as a former graduate student and current educator. These stories focus on pedagogical practices, dynamic identity formation and reflective engagements with place as valid and vital ways of knowing, doing, being and becoming. I highlight how choice often entails challenge, how agency and struggle can be intertwined with empowerment, and how marginalisation can coexist with celebration. This inquiry aims to reveal the layered complexity and sometimes paradoxical dimensions of learner and teacher identities within the assemblage of learning and teaching in higher education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".