<i>Shadowpox: The Antibody Politic</i> – Thoughts and Reflections
Bibliographic record
Abstract
This dialogic exchange discusses the development and outcomes of an interactive installation that uses live-animated digital effects to projection-map viral “shadowpox” onto the player’s body. The project was developed by Alison Humphrey, then a Vanier Scholar and York University PhD candidate in cinema and media studies, in collaboration with Caitlin Fisher, director of York University’s Immersive Storytelling Lab, and Steven J. Hoffman, director of the Global Strategy Lab and scientific director of the Canadian Institutes of Health Research’s Institute of Population and Public Health, with support from technical director and creative coder LaLaine Ulit-Destajo, epidemiologist Susan Rogers Van Katwyk, and website programmer Sean Sollé, as part of the three-year interdisciplinary project , and culminated with an exhibition at UNAIDS during the 70th World Health Assembly in Geneva, Switzerland.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".