In search of home on landscapes in transition: narratives of newcomer families' cross-cultural schooling experience
Bibliographic record
Abstract
This is a study of newcomer families in search of home in Canada on landscapes in transition. My 3-year intensive fieldwork and 2-year follow up at Bay Street Community School, an inner-city school in Toronto, helped me develop a narrative understanding of linguistically and culturally diverse school life. Narrative methodology enables me to simultaneously study the cultural tensions and communications in the processes of cultural adaptation while appreciating the knowledge and values brought to Canada by new immigrants. I offer a concept of generational family narratives and use generational narratives as the lens to construct immigrant educational profiles of five families. I interpret these profiles as culturally and personally embedded expressions of Confucian philosophy and I make comparisons with Deweyian experiential philosophy. I explore the curricular significance of these family narratives by using Schwab's practical concept of curriculum. I found that Chinese families' notion of home is closely related to their notion of learning, which is deeply rooted in Confucian thought. Chinese grandparents' and parents' dedication to the family and their efforts and sacrifices for younger generations are, from the Confucian perspective, contributions to family harmony, and hence to the harmony and growth of society. Through the lens of generational narratives, my study reveals both hidden needs and special contributions. It also shows that Canadian society is constantly reshaped and reconstituted by newcomers' cultural interactions with and adaptation to the existing society. People thought of as the mainstream or those who have adapted to the mainstream need to see themselves as part of the adaptation process in the changing landscape. This reciprocity can help contribute to a society that is multicultural and inclusive for all. Generational narratives provide insights for cultivating 'we-consciousness' in diversity, a vision intended to embrace linguistically and culturally diverse school life in narrative unity: Confucian continuity of being and Deweyian continuity of knowing. The study calls for extended and expanded mutual we-ness in dialogues across civilizations in hopes of building a multidimensional bridge that can harmoniously connect ethnically, socially, culturally, and linguistically diverse people. Hence our children can grow up in positive multicultural harmony in diversity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".