Bibliographic record
Abstract
This exposition posits art as a form of contagious divination, a glimpse into the multiplicity of possible futures, and an examination of artists' ability to detect momentum towards unavoidable outcomes. In 2014, I was selected by curator Heather Pesanti to participate in the City of Toronto’s annual Nuit Blanche festival, an overnight public art event spanning twelve hours in multiple neighborhoods that draws over a million people from the surrounding regions.Spurred by my concerns about the inescapable gravity of mobile electronic media and "viral culture," my work was to be a performance premised on contagion, pointing to the monumental role that electronic media had assumed in mediating our direct experience, and the civic and societal fallout I believed would ensue. Little did I suspect how bizarrely prescient the work would turn out to be.On October 6th, 2014, one hundred glowing “carriers,” dressed in fluorescent hazmat suits, wearing fluorescent LED-wired helmets in the dodecahedral geometric shape of an adenovirus, dispersed throughout the City of Toronto, each "testing" and “infecting” at least one hundred festivalgoers by marking their faces and hands with “spots” “lesions” and “rashes” using surgical swabs dipped into a beaker of invisible UV-reactive ink. Each "test subject" was then gifted a small UV pen lamp with built-in reactive ink marker and instructed to "infect" and "test" ten others.It is estimated that HALFLIFE attained an "R-naught" value of ten, and through this performance, affected approximately one hundred thousand people.Images of the performance went viral on Instagram for seventy-two hours, during which Toronto General Hospital admitted their first and only suspected Ebola case. keywords: contagion, performance, Performance art, Sculpture, artwork, artistic research, art process, art practice, public art, public urban art, public engagement, relational aesthetics, relationality, Virus, viral media, contagious, contamination
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.559 | 0.359 |
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".