Migrations and expression of transnational design in a globalized world
Bibliographic record
Abstract
This study examines two case studies by final-year students at York University, Toronto, Canada. These students are both of Chinese descent, with parents who migrated from Hong Kong to Canada at different times. The first case study is a language learning kit designed by a student born in Canada and whose parents migrated in the 1970s. She speaks little Cantonese, and this project reflects her experiences learning the language. The second case study is a research and book design project on design elements of Chinese restaurants in North America. This student, who migrated with her parents in the 1980s, has a better command of Chinese. With greater knowledge of Chinese cultures and language, this project can be viewed as a search for Chinese identity in a Western context through a very common sight for the student: Chinese restaurants. This paper argues that these two cases represent different degrees of investigation of transnational visual design languages, created by the students in an unplanned way. Further discussion will center on questions dealing with the contemporary reception of Chinese cultural elements in the context of a globalized world, and inquire as to whether its visual expression forms can become an international design style in the future. This study contributes to the emergence of transnational design in the global context, a topic that is currently underdeveloped in world design education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".