Bibliographic record
Abstract
T hrough the media of photography, perfor mance, installation and video, the group exhibition Auto/Pathographies addresses questions of identity and (self-)representation in the face of illness.Bringing together wor ks from 10 ar tists based in Canada, the U.S., the U.K. and Austria produced from the 1990s until today, the exhibition offer s both sensitive and critical per spectives on the roles played by disease in redefining individual existences and inter per sonal relations.Amongst these wor ks are a number of rare images from the Jo Spence Memorial Archive.Ear lier this year, Spence was the subject of two retrospectives in London to mar k the 20th anniver sar y of her death.Auto/Pathographies features Spence's photographic explorations of mor tality from her series The Final Project, shown here for the fir st time in Canada.With these, and each of the ar twor ks presented in Auto/Pathographies, sickness is tr ansfor med into a site of active aesthetic, political, and even metaphysical inquir y, one whose interest extends well beyond that of the individual subject's nar rative.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.109 | 0.015 |
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".