Bibliographic record
Abstract
Horizon Cross: A Parafictional History Through Photographs is a body of work that dwells within the intersection between truth and fiction in photography. It is informed by the history of hoax photographs and my fascination with the Large Hadron Collider in Switzerland and black holes, the space-time boundary of which is known as an event horizon. I have imagined into being a community in northern Ontario Province, equipped with the technology of the mid-nineteenth century but also with concepts far ahead of their time. To portray the inhabitants of Horizon Cross I have created photographic portraits of fictional people that I am presenting as cabinet cards, in order to reference a specific moment in time through the use of historically appropriate photographic processes as well as to explore portraiture and create photographic artifacts. I have combined historically appropriate imagery in the cabinet cards with imagery unique to Horizon Cross. Like my concept of fact and fiction, my technical process is a hybrid of modern digital and traditional chemical based photography: it is important that the cabinet cards are albumen prints mounted on cardstock that have been letter pressed with era appropriate graphic design and fonts. While I may have created the individual portraits, I have assembled them collectively as evidence of the existence of Horizon Cross.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".