Bibliographic record
Abstract
I was a 2017-2018 Centre for Mobilities Research CEMORE Visiting Fellow, Lancaster University. I worked closely with the Director of Mobilities Lab Dr Jen Southern, as well as Professor Emma Rose and Dr Linda O Keefe of the Lancaster Institute of Contemporary Arts, and successfully co-curated the Art & Mobilities Network Inaugural Symposium. The study and practice of Art & Mobilities has been gaining momentum in the past decade. This includes pioneering solo and collaborative work led by Jen, a key player in the field. The Art & Mobilities network consolidates, celebrates and develops this work. On 3rd July, nearly thirty artists, writers, curators and researchers gathered at the Peter Scott Gallery. Apart from UK-based colleagues like Nikki Pugh, Elia Ntaousani, Bruce Bennett and Bron Szerszynski, we were joined via Skype by Mimi Sheller (USA), Owen Chapman (Canada), Kaya Barry (Australia) and Sven Kesselring (Germany). UK participants brought with them objects, images or texts for a pop-up exhibition. We wrote our big ideas on a ‘manifesto wall’ and considered the histories of mobilities in art practice through a timeline running across the Gallery. Jen gave a keynote packed full of information and provocations covering creative research methods, the aesthetics of mobility and so on. We closed the colloquium with a role and ‘next step’ that each of us intends to perform to get the group going. In the longer term, we will seek funding to build this network internationally and to facilitate collaborations and activities such as conferences, exhibitions and publications.I also gave a keynote lecture which was a performance-lecture of how art and mobilities collide for me as an artist, curator and woman. In addition, I collated an ‘instant journal’, an experimental platform which documents some of our activities and thoughts, and which we will continue to edit and develop.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.341 | 0.141 |
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".