Ephemeral Art: Telling Stories to the Dead
Bibliographic record
Abstract
Abstract: The endurance of the form of storytelling and the compulsion to tell them suggests that telling stories is not merely an entertainment, an optional extra which we can chose to engage with or not, but a fundamental aspect of being. We tell stories to construct and maintain our world. When our sense of reality is damaged through traumatic experiences we attempt to repair our relationship with the world through the repeated telling of our stories. These stories are not just a means of telling but also an attempt to understand. Stories are performed and performative; they do not leave us unchanged but can in fact motivate us to act. They are not merely about things that have happened, but are about significant events that change us. Through our stories we demonstrate that we have not only had experiences but that those experiences have become part of one’s knowledge. In this essay O’ Neill will explore the potential of objects to tell a story, the object that is both the subject of the story and the form of telling. Two ephemeral art works will be considered: Domain of Formlessness (2006) by British artist Alec Shepley and Time and Mrs Tiber (1977) by Canadian artist Liz Magor. Both works embody the process of decay and tell a story of existence overshadowed by the knowledge of certain death and the telling of the story as a means of confronting that knowledge. The ephemeral art object tells a story in circumstances when there are no words, when we have nothing left to say.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".