Bibliographic record
Abstract
The anamorphic cinema is a research/creation project that proposes new ways to engage with moving images by applying digital imaging and animation to catoptric anamorphosis, a perspectival technique from the seventeenth century that deforms pictures so they appear to re-form in the reflection of a curvilinear mirror. Culminating in Ghost in the Machine: The Inquest of Mary Gallagher, a looping fifteen- minute, site-specific video installation investigating the culpability of a working class woman in the 1879 murder and beheading of another, this project problematizes representation as re-presentation. Dramatic performances of witness testimonies and newspaper texts, layered with diverse archival images form a network of narratives that revise the case within a context of nineteenth-century spectatorship, visual culture and disciplinary discourses. Made for exhibition in the historic Montreal neighbourhood called Griffintown, the location where the events it depicts took place, Ghosts emplaces and embodies multi-perspectival views, encouraging mobile spectatorship and passive interaction. Audience members cannot alter the work directly but their experiences are dependent on their relative positions and angles of view. The anamorphic cinema literally re-presents partial perspective and situated knowledge, materializing theory into phenomenological practice.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".