The Triangle Arts Trust: Contemporary - Art and Transnational Production
Bibliographic record
Abstract
This dissertation presents a historical overview and contemporary analysis of the Triangle Arts Network, an international network of artists and arts organizations that promotes the exchange of ideas and innovation within the contemporary arts. It was established in 1982 through a workshop held in Pine Plains, New York and quickly grew into an international network of artist led workshops around the world. More than twenty years later the network continues to grow and includes a roster of ongoing workshops as well as artist led organizations and centres. This dissertation situates Triangle as a major global phenomenon, yet one that operates outside the mainstream artscapes. My research follows the networkâ s historical links from Saskatchewan, Canada, to New York and onto South Africa. This web-like evolution demonstrates the complexity of global art networks and the fluidity of boundaries needed for contemporary art discourse. This research explores how the movement of ideas, artists and infrastructures complicate our understanding of clearly defined boundaries within contemporary art and globalization. Using Actor-Network Theory (ANT) as a metaphor for the Triangle Network, I attempt to unpack the complexities of an art system without objects, a process without product and the entangled relationships between artists, workshops and grassroots models of production.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".