Bibliographic record
Abstract
Between 11 September and 8 December 2019, Syrus Marcus Ware’s multi-channel video work Ancestors, Can You Read Us? (Dispatches from the Future) was on view at the Ryerson Image Centre in Toronto. The video, created with Mishann Lau, features performers Kyisha Williams, Rodney Diverlus, Raven Davis, Janine Carrington, Ravyn Wngz, Gloria Swain, and Jasmyn Fyfe, imagines and stages a dialogue with a future beyond the current epoch of Black social death and insecurity and this time marked by the ever-present capitalist forces of greed and the persistent script of police and state violence. In this piece, written as a companion to the video installation, Ware not only meditates on the precarity of the present but also insists on the necessity for social change through an imagining of the collapse of capitalism and the radical time after with a social restructuring of forms of relations and care. This work draws on the Black speculative, futurist, vision of our ancestor, Octavia Butler, to sketch a radical Black queer imagining of the future—one that queers time, survival, family, and relations to articulate an abolitionist vision as the way forward.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.133 | 0.026 |
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".