Bibliographic record
Abstract
The digital image, Death of a Cyborg (2010) by Canadian artist Shorra (Deborah Mason), that appears on the cover articulates many of the ideas about touch and technology explored in this book. Unlike many popular fiction images, this is not an image of a rogue cyborg crushed in an industrial press or submerged in molten steel. Instead it shows a grieving human male/female couple with the partly destroyed cyborg (end of one arm missing, covering of neck, abdomen and knee removed so that its circuitry is showing) lying across the man’s knees. The style of the work is High Romantic and it is, in fact, a digital update of William Adolphe Bouguereau’s painting, First Mourning (1888), which depicts Adam and Eve mourning the death of their son Abel, who was killed by his jealous brother, Cain; so the painting also depicts the first murder. The pose of the figures attests that their relationship was intimate, the woman pressing herself against the seated man’s chest under his protective outstretched arm while the cyborg lies across his thighs, the man’s other hand stretched across his heart as if to indicate overwhelming grief. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.439 | 0.215 |
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".