Bibliographic record
Abstract
Future Collective for Our Past Sorrows is an experimental multi-media installation that examines the spectral presence of the Yangtze River dolphin. This work includes documentation from my fieldwork at the Institute of Hydrobiology, Chinese Academy of Sciences, in Wuhan. There, I traced the ghostly presence of the Yangtze River dolphin, examining the now-abandoned pool where Qiqi, the last known Baiji dolphin, once lived. The objects in the exhibition are drawn partly from the Institute, with others borrowed from and given by the Oxford University Museum of Natural History. A soundtrack of a fictionalised curator's narration accompanies the piece. My fieldwork prompted a few questions: what if the story were told from the perspective of the dying Baiji dolphin? What if I hypothesised that his memories lingered long after his passing? That somehow, his spirit still lived in the pool, allowing us to meet? This project seeks to understand what happens to conservation efforts and the memories they engender when care and attention run out.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.097 | 0.015 |
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".