Bibliographic record
Abstract
As can be expected, organizing a large international exhibition with global ambition requires some proximity to various scenes of artistic production scattered in near and far-flung corners of the globe.An important requirement for the curator or researcher working to know these artistic scenes, entails being equally alert to the dark murmurings in the cultural and political scenarios that are adjacent to the spaces where the activities of art occur.For example, to reach artists working in Havana from New York necessitated passing through Toronto, thus exposing one such political scenario, namely that artists and curators living on each side of the dividing walls of the U.S./Cuba ideological separation must constantly negotiate.My several trips to Cuba for more than a decade have invariably involved the kind of triangulation that requires passing through way stations such as Montego Bay, Mexico City, the Bahamas, and Toronto.My recent visit was no different.In all these tripsfrom Havana to Caracas, Singapore to Berlin, Seoul to Beijing, Mexico City to New York, Cairo to Mumbai, Sydney to London, Kuala Lumpur to Istanbul, or taking the ferry from Tangier to Tarifa-one witnesses not so much a change of geocultural agendas, as much as witness, especially as the trip to Havana shows, the accelerating ideological irrelevance to which many of these diverse geopolitical spaces once subscribed.During this period, I spent most of the time preparing for the 7th Gwangju Biennale by visiting artists; speaking with writers and filmmakers; visiting galleries, art schools, and assorted cultural brokers.Otherwise, I lie awake in hotel rooms, many of which appear no different in design, ownership, and amenities than the ones in
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".