Bibliographic record
Abstract
Four pairs of images from the Postcards from the Underground (2022) print series are presented here as experiments in translating invertebrate underground worlds. Artist Perdita Phillips and cultural theorist Astrida Neimanis collaborated to create an interdisciplinary ‘walkshop’ event to the coal mining town of Lithgow, as part of Phillips’ Artsource both/and artist in residence at Artspace, Sydney in 2017. The many forms of stygofauna—small invertebrate animals including worms, mites, snails, insects and many crustacea—can be found in the millimetreswide in-between spaces in groundwater. Short-range endemism is common—due to their distribution in isolated patches beneath semi-arid to rainforest landscapes in Australia—and sporadic relic distribution world-wide. Working between Neimanis’ text and Phillips’ drawings and found images, the conversations with and through stygofauna, underground water and mining were then developed into colour postcards, that use a red/cyan optical masking technique. The images can be decoded with a red filter that is held up to the eye. The previously invisible cyan delineations are then revealed from beneath—alluding to the layers of concern and the double state of both/and—“caught up in both the noticing and notnoticing of each other” that the artist/author were articulating (Neimanis and Phillips 137). The swirling patterns of swimming and the complex fingering of many limbs were rendered into cryptic scores. The postcards explore notions of hiding/revealing and comprehension and miscomprehension of subterranean ecosystems, through the multiple scratchings of the skittering limbs of stygofauna. Phillips, Perdita and Astrida Neimanis. Postcards from the Underground. 2022. Private Collection.
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 | 0.001 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.598 | 0.453 |
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".