Unfolding Artistic Practices — with Laura Marks
Bibliographic record
Abstract
Below the Radar explores unfolding the enfolded with Laura U. Marks, an SFU professor and scholar who works on media art and philosophy with an intercultural focus. She is in conversation with co-hosts Am Johal and Paige Smith about her research into experimentalism and aesthetics in Arab cinema and the connections between Islamic art and philosophy and new media art. Laura talks about co-founding the Substantial Motion Research Network, tracing cultural and artistic genealogies, and de-westernizing artistic practices. They also discuss the concerns around the environmental consequences of streaming media that led Laura to create the Small File Media Festival.\n\nLaura U. Marks works on media art and philosophy with an intercultural focus. She programs experimental media art for venues around the world and is the founder of the Small File Media Festival. Laura's most recent books are Hanan al-Cinema: Affections for the Moving Image (MIT, 2015) and Enfoldment and Infinity: An Islamic Genealogy of New Media Art (MIT, 2010). With Azadeh Emadi she is a founding member of the Substantial Motion Research Network of artists and scholars working on cross-cultural approaches to media technologies. Marks is Grant Strate Professor in the School for the Contemporary Arts at Simon Fraser University in Vancouver.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".