Bibliographic record
Abstract
I’m a first-generation Canadian who was born and raised in Toronto, Ontario by Asian immigrants. I have migrated to the United States and lived here for 7 years. Through my work, I express the emotional value of preconceived notions, disconnectedness, and longing in search of finding place and acceptance within a community. Drawing from memory, personal narrative, emotion, and perception, I manipulate data into lines, forms, and materials through a subjective human experience from the lens of a non-citizen. By projecting the migration movement of my family lineage from China and the Philippines to Canada as well as my path to the United States, I am deconstructing and reconstructing meaning and purpose of fragmented identity. Through the use of statistical data that represents migration patterns, my own identification number, and metaphors around borders and access, I am exploring representations of phenomena, displacement, belonging, and defeat as a response to social and cultural order. Through my formal training as a woodworker, the work aims to communicate sympathy through hardship, accessibility, and the desire of a migrant finding place. I produce aesthetically engaging sculptural forms made from reclaimed solid wood, found materials, and domestic construction building materials at an architectural scale.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".