From Multiculturalism to Transculturalism: Constructing Meanings of Transcultural Learning as a Transformative Process
Bibliographic record
Abstract
Canada is often held up internationally as a successful model of immigration and multiculturalism. For over half a century, multiculturalism as national policy and normative framework has been the subject of discussion focusing on social divisiveness, clash of cultures, and ethnic marginalization and stratification. Recent debate has shifted to the future of Canadian multiculturalism in an age of transnational migration and hyperdiversity characterized by multiple and circular movement across transnational spaces. Critiques claim that Canada's official multiculturalism is showing signs of crisis since it is no longer theoretically attuned to the demands of a rapidly changing and highly mobile complex world. As an alternative, transculturalism has been presented as a more complex mindset reflecting the dynamic interplay, diversification of diversity, and multiversality of belonging. Drawing on the concept of transculturalism, this article explores how people constructed meanings of transculture and transcultural learning out of their lived experiences in an era of transnational migration. Findings from a qualitative study reveal that transcultural learning is a holistic and transformative process that connects local to global, challenges taken-for-granted frames of reference, expands worldviews, integrates new practices, and transforms individuals. A holistic transformative approach of transcultural learning takes into consideration the stabilizing or destabilizing effect, social conjunction, historical conditions, integration or disintegration of groups, cultures, and power experienced on micro, meso, and macro levels.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".