Bibliographic record
Abstract
ç eli k ale x an d er A n epistemological transformation has been taking place in architecture schools across North America: the nature of evidence marshaled in the design studio has been quietly changing.1Two decades ago students pinned up analyses of historical precedents during reviews to account for their design work.Today the same walls are covered instead with flow diagrams on energy consumption, images of brain scans, maps of transportation networks, or models of thermal distribution.The most extreme illustration of this attitude might be evidence-based design.2These tables, diagrams, and maps visualize a different kind of evidence: 'data' in its various guises.One recent commentator evaluating the role of the precedent in today's architectural education even suggested that the planet might have become the "ultimate precedent" in design schools (Carver, 2011:81).The architectural theorist Colin Rowe, who once compared the architect to a lawyer who could not use his faculty of judgment in the absence of an inventory of historical precedents, would have been scandalized (Rowe, 1996).This is certainly not the first evidentiary regime change that architectural discourses have seen.In the West alone, the last century was marked by several such changes.Modern design education, as it developed in the early 20th century at institutions such as the Bauhaus, was predicated on a late-19th-century formalism for which 'lived experience' was the primary evidence.As the language of space replaced the academic terminology of orders and proportions, upheld by the authority of Classicism, the body's response to 'form' became to be established as the acceptable method of justifying design (Jarzombek, 2000).Design training at
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.015 |
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".