Tales from a Hospital Entrance Screener: An Autoethnography and Exploration of COVID-19, Risk, and Responsibility
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This autoethnography explores my experiences as a hospital entrance screener during the first wave of the pandemic in a hospital in Ontario, Canada. In April 2020, I was redeployed from my research role to a hospital entrance screener. Focused on my lived experiences, the purpose of this research is to provide a glimpse into what it was like to work in a hospital early in the pandemic, to understand these experiences in relation to sociocultural meanings, and to try to make sense of my experiences with COVID-19. Through reflections, I offer a critical account of my experiences working as a screener and analyze personal reflections about my thoughts, feelings, and experiences from a post-structural lens. My analysis reveals several themes: responsibilization, risk, emotional labor, policing and securitization, and the hero discourse. My experiences as a screener demonstrate the complexities of the COVID-19 society and experience.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it