Bibliographic record
Abstract
Under the title Symphony for Absent Wildlife Professor Lucy Orta has created a true ode to wildlife, taking the form of a visual and audio installation, presented at the Nuit Blanche in Calgary in Canada, curated by Wayne Baerwaldt. In Symphony for Absent Wildlife, the stretcher-bed - an occurring metaphoric object in Orta’s practice - marks a pathway to woodland clearing, composed of weathered tree trunks sourced from local forests, an essential zone for the maintenance of forestry biodiversity. The path is raised above the ground by the means of simple wooden trestles, the kind constructed for chopping wood. In the clearing, we encounter a masked orchestra of Spirits. Each Spirit musician dons a mask in the form of a woodland creature, and an iconic tailcoat tailored from reclaimed felt blankets that bare the inscriptions of past warriors and homeless wanderers. The blanket represents an element of exchange between First Nation communities and the first European traders and settlers, and it became a 'democratic' item of clothing. Wearing blankets, Orta's foreboding masked figures recall the spirits of the once abundant wildlife across the Albertan plains: bison, moose, wapiti, wolves, grizzly bears, and eagles. The music stands illuminate a graphic score, the conductor guides the masked-animal musicians, and the performance commences. An amplified symphony of avian chatter - birdsong - resonates across the city. Man or beast? Just simple hand crafted bird whistles that replicate the remarkable sounds of nature. Symphony for Absent Wildlife brings a fragment of the disappearing natural environment, its sounds and the diversity of its fauna, closer to the city. Research was undertaken in the Glenbow Museum Calgary, and included discussions with local inhabitants, academics and students from Alberta College of Art and Design. The process was complemented by a 6-month workshop with the graduate community at the University of the Arts London.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.168 | 0.026 |
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".