On the Question of Objects –“Imagined Field from the Deconstruction of an Apparatus”
Bibliographic record
Abstract
This text is an artistic companion to the accompanying collages where complexity, ambiguity, emergence, and abstraction are emphasised. Through artistic practice I investigate the primacy of objects and their relations. Consistent with Barad’s Agential Realism, objects are constructed through their relations. This conflicts with a capitalist and colonialist view where objects pre-exist relations and are that which can be extracted, used and/or consumed. The images herein are composed from fragments of photographs taken at a particle accelerator facility where fragment boundaries are constructed by a machine learning algorithm. Images are composed by placing fragments according to their relationships using a second machine learning algorithm that emphasises some boundaries and dissolves others. These layers of boundary-making are analogous to cognitive processes where the objects of thought are proxies for complex relations. This is the crux of our contemporary era; social and material complexity cause us to attend to objects at the detriment of the systems that allows those objects to be.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.093 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".