Doing nothing does something: Embodiment and data in the COVID-19 pandemic
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
The COVID-19 pandemic redefines how we think about the body, physiologically and socially. But what does it mean to have and to be a body in the COVID-19 pandemic? The COVID-19 pandemic offers data scholars the unique opportunity, and perhaps obligation, to revisit and reinvent the fundamental concepts of our mediated experiences. The article critiques the data double, a longstanding concept in critical data and media studies, as incompatible with the current public health and social distancing imperative. The data double, instead, is now the presupposition of a new data entity, which will emerge out of a current data shimmer: a long-sustaining transition that blurs the older boundaries of bodies and the social, and establishes new ethical boundaries around the (in)activity and (im)mobility of doing nothing to do something. The data double faces a unique dynamic in the COVID-19 pandemic between boredom and exhaustion. Following the currently simple rule to stay home presents data scholars the opportunity to revisit the meaning of data as something given, a shimmering embodied relationship with data that contributes to the common good in a global health crisis.
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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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