Art in the Archives of Natural History: The Temporalities of Spoerri’s <i>Ein Inkompetenter Dialog?</i>
Bibliographic record
Abstract
The essay analyzes contemporary artist Daniel Spoerri’s 2012 retrospective exhibition, titled Ein Inkompetenter Dialog?, held at the Vienna Natural History Museum (NHM). The exhibition comprised a selection of works from Spoerri’s œuvre shown alongside a selection of the Museum’s specimens. I argue that juxtaposed with the Museum collection, Ein Inkompetenter Dialog?, both as a collection of works and as an archive of the career of the artist, playfully calls into question the “nature” of art, the presentation of nature in the NHM, and the temporality of the archive and natural history. Much of Spoerri’s œuvre involves the reworking and assemblage of his own collections of found objects. I argue that these imaginative assemblages, which merge human and non-human life, present concrete visions of possible alternative natural histories and prompt us to rethink natural history from a multispecies perspective, where humans and non-humans function as co-agents, and where history and natural history are fused. Overall, I argue that Spoerri’s creative exploration of the material archives of natural history presents an alternative approach to re-collecting the past, and the possibility of writing history for a non-anthropocentric future.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.028 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".