The legacy of the Ecole des Beaux-Arts in the formation of North American Deco
Bibliographic record
Abstract
In cities as far afield as Brussels, Tunis, Montreal, Rio de Janeiro, and Shanghai, the diaspora of architects classically trained at the Paris Ecole des Beaux-Arts orchestrated, popularized, and interpreted Art Deco with elegance and panache. This chapter presents a larger study of the combined design acumen and social leverage of the “Beaux-Arts architect” in the US and Canada. It reviews Beaux-Arts tenets and strategies applicable to Deco work by focusing on spaces of consumption and leisure, comprehended as transatlantic typologies; their Parisian frame of reference is manifest, and their design was dictated by branding and visual agenda. Steadily produced since the 1980s, publications on Ecole-trained architects in North America still amount to the tip of the Beaux-Arts iceberg. In 1924, Jacques Carlu was hired as MIT’s chief design critic on the strength of his 1919 Grand Prix de Rome, but also for his charisma, youthful enthusiasm, and possibly his athletic stature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".