Bibliographic record
Abstract
OST, 29th - 30th September 2023, OPENing, 11 Angel Court, Moorgate, London EC2R 7HB. Participating Artists: THOMAS ALLISON, RIHANATA BIGEY, DAWN CODEX, COMPOUND 13 LAB, IAN DAWSON, ESI ESHUN, DARBY HERMAN, JOSEPH IJOYEMI, LENNON MHISHI, LOUISA MINKIN, RABIYA NAGI, ADANMA NWANKWO, CHARLES NYIHA, DESERAE TAILFEATHERS "We are ghOSTed. Reflectance Transformation Imaging makes visible the timespace of the erased and overlooked. We are haunted in this old underground bank at the heart of the City of London by hOSTs of ghOSTs. The building is a shell holding itself up by memory, being prepared for regeneration. Lost rivers echo in the basement. Traces of past occupation point to the future, divining by acronym: Open Source Threat, Outer Space Treaty, Observed Survival Time. For the past year we have been working and talking, thinking about material culture, cultural capital, power and estrangement. We’ve visited with entities in museum stores, jumped time zones and calibrated calendars to make connections. We present here actions, images, sounds and objects On Second Thoughts.. Original Sound Track… OST is a project developed by participants in the Prisoners of Love project. Prisoners of Love: Affect, containment and alternative futures [funded by the AHRC GCRF project Imagining Futures] aims to connect UK museum collection items with their trans-national home peoples and bring emerging artists from diasporic communities in the UK, curators and researchers into conversation, to work responsively with complex histories and material practices, opening out extra-institutional art and archival practices in the form of artwork, story and theory. We have been working with the Horniman Museum and Gardens and Compound 13 Lab in Mumbai, India; Pitt Rivers Museum, Oxford and the Department of Archaeology at the University of Ghana in Accra; Hastings Museum and Art Gallery and the Mootookakio’ssin project based on Blackfoot homelands at the University of Lethbridge, Canada. This exhibition contains responses from the UK team, partners on Blackfoot Territory and Compound 13 Lab in Mumbai, India and works towards further collaborations."
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.726 | 0.366 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".