Intersectionality in mathematics and the arts: honouring the memory of Reza Sarhangi (1952–2016)
Bibliographic record
Abstract
Reza Sarhangi (1952–2016), as a mathematician, educator, and artist, had a profound impact on many interdisciplinary approaches to the study and teaching of mathematics and the arts. His vision and enthusiasm embraced and energized an international community of individuals engaged in explorations of intersections of art and mathematics. His legacy lives on despite his unexpected and premature death. He is best known for the success of his visionary endeavours surrounding the establishment of the Bridges Conference (Mathematical Connections in Art, Music, and Science), which has been transformative in the fields of math and art. With the great breadth of his interdisciplinary interests, coupled with his love of engaging people and ideas, he founded Bridges on a model developed by Nat Friedman, professor of mathematics at the State University of New York-Albany, for art–math conferences (1992–1998). Since its founding in 1998, Bridges has met annually, attracting an ever larger cadre of artists, mathematicians, teachers, computer scientists, and the occasional art historian. Bridges began when Reza was teaching at Southwestern College in Winfield, Kansas, and it moved with him when he moved to Towson University near Baltimore, Maryland. Subsequently, Bridges expanded globally with academic collaborations that Reza negotiated with colleagues and their institutions in Granada, Spain (2003), Banff, Alberta, Canada (2005), London, United Kingdom (2006), Donostia, Spain (2007), Leeuwarden, The Netherlands (2008), Banff, Alberta, Canada (2009; ), Pécs, Hungary (2010), Coimbra, Portugal (2011), Enschede, The Netherlands (2013), Seoul, South Korea (2014), Baltimore, Maryland, USA (2015), Jyväskylä, Finland (2016), and Waterloo, Ontario, Canada (2017), which marked the 20th Bridges Conference. Papers, published in annual proceedings, are archived and available online
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".