Final Project : Parallels between Pottery and My Identity as a Second-Generation Chinese Growing Up in Canada
Bibliographic record
Abstract
A common experience among minoritized artists is the internal struggle associated with creating art that is traditional to their culture. For example, a Chinese Canadian artist might want to showcase Chinese styles in their art because that is what best represents them; however, the question of whether one is “enough” of that minoritized culture to even use that style often comes up. It makes them question whether they have the credibility to use such cultural styles, and whether they would be seen as merely appropriating a style that they don’t have enough credibility to use. And does using that style create the perception that their usage signals representation? This all creates additional pressures on the artist to do a really good job, lest their potential failure reflects poorly on their entire community. With all of these pressures, though, it is still imperative that minoritized artists push forward and create a style that is their own. Dive into Amalee’s thought process as she discusses similar struggles while creating two ceramic vases to represent her and her brother. If you were in a similar position, how would you reconcile the need for representation with the worries about being too much of an imposter to engage in representation?
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.050 | 0.017 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".