Bibliographic record
Abstract
For me, rhythm means having consistency. The piece highlights my own experience with the disruption of my daily rhythm due to COVID-19. The first half shows my routine and interactions prior to COVID-19 while the second half shows my experiences in the present day. Prior to the virus, I had a day to day routine that was filled with noise. Everyday moved quickly and I established a daily rhythm. However, when COVID-19 spread, it changed everything. I felt like I didn’t have a routine anymore because I wasn’t allowed to go anywhere. Time was moving much slower and worst of all, xenophobia was growing at a significant rate. As a Chinese Canadian, this was the first time I truly felt the weight of the color of my skin. COVID-19 changed the way that I consistently assumed that the color of my skin wasn’t something that strangers would significantly care about. However, as I got on a bus, I unintentionally scared a woman simply because of my skin color. From that point, I knew that xenophobia would affect the way people perceived me everyday. The woman was scared of the virus— which in turn was scared of me—and I was scared that she would thwart her anger towards me because I am Chinese. If looks could kill, then the woman and I ironically both feared each other. Now, due to COVID-19, I am adapting to a new routine. A routine where the color of skin rings louder than any other sound.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".