Bibliographic record
Abstract
The Under the Radar festival is the result of the politics of a time and place that were reset by 9/11. That is when the USA finally learned that it is not invulnerable at home and that its alliances in art, culture, science, and industry are fundamental to its well-being. Situated at Astor Place, a neighbourhood at the crossroad between New York’s East and West Village, Under the Radar is part of a long history of a place that maps part of the story of American immigration, architecture, urban decay and renewal, the economy, and theatre. The festival pivoted away from American exceptionalism towards the interdependence of the neo-liberal economy by accentuating transnationalism in the context of globalization. Greenwich Village’s intellectual and artistic vibrancy has a history of being in conversation with ideas and experimentation originating in Europe, Asia, Africa, Australia, and the Americas. Under the Radar draws upon and adds to this legacy of place through its presentation of work from all over the world. Diversity at Under the Radar signifies ‘this is us’, not in the sense of either multiculturalism or sameness, but of an inquiry of ideas that shapes our shared human destiny.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.141 | 0.019 |
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".