Bibliographic record
Abstract
The year 2008 was one of fruitful disjunctions. I spent the fall teaching at Stanford but commuting to the University of California, Los Angeles, to cochair the inaugural Mellon Seminar in Digital Humanities. During the same period, I was curating—at the Canadian Center for Architecture, in Montreal—an exhibition devised to mark the centenary of the publication of “The Founding Manifesto of Futurism,” by Filippo Tommaso Marinetti. Whereas other centennial shows (at the Centre Pompidou, in Paris, and at the Palazzo Reale, in Milan) sought to celebrate the accomplishments and legacies of Marinetti's avant-garde, the Canadian exhibition,Speed Limits, was critical and combative in spirit, more properly futurist (though thematically antifuturist). It probed the frayed edges of futurism's narrative of modernity as the era of speed to reflect on the social, environmental, and cultural costs. An exhibition about limits, it looked backward over the architectural history of the twentieth century to look forward beyond the era of automobility.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.033 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.021 | 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".