Bibliographic record
Abstract
Jeremy James is a Canadian-born, Australian-raised artist based in Europe, who has worked across a diversity of media to explore his interests and concerns with the relationship between representation and meaning. His early visual art practice was driven by a critical and deconstructive eye, particularly with reference to personal and cultural identity. Jeremy will discuss the ways in which his initial investigations at art school set the foundations for a career that has evolved predominately into theatre and performance. Having initially studied at the Canberra School of Art in the early 1990s, Jeremy has worked as an actor, director, artist and teacher across the performing and visual arts. His interest in interdisciplinary practices lead him to Europe to further train with leading artists and teachers. He has developed a unique approach to contemporary performance which is informed and inspired by his early experience and training as a visual artist. Most recently, he was a member of Ariane Mnouchkine's renowned theatre ensemble, Le Theâtre du Soleil in Paris. He collaborated on all aspects of the company's epic-projects, Le Dernier Caravanserail and Les Ephemeres, from design and development to production and performance. He has toured extensively to major theatres and festivals internationally and received critical acclaim for his work. He has been invited to give workshops in France, Spain, UK, Canada, Argentina and Brazil, while teaching and leading masterclasses for actors and directors at drama schools and universities in Europe.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.429 | 0.157 |
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".