Bibliographic record
Abstract
Digital tools in architecture have a powerful capability that we have only begun to explore; the questions to ask of them are perhaps not what they can do but what should we use them for? To date, much of the work done in the area of computational design has been used as elaborate patterning - some have called it ‘ornament’. The significance of this ornament is not only pleasure but in its use of digital patterns to represent our current complex and digital age. This representation in itself is not problematic; however, what is problematic is the lack of other meaningful uses of the digital form-generating tools and their distance from a culture of making. The main failing of our use of digital design (algorithmic or not) in architecture to this point is its inability to translate smoothly from the digital world to the physical world. The main reasons for this difficulty in translation are gravity and inherent material properties. Working with gravity and its physical implications is generally considered the role of the structural engineer; as such, engineers have generally created digital tools in this area. The engineer's methodology analyses a structure based on complex structural analysis programming but in order to do this, a detailed description of the structure must already exist. This is not useful in preliminary stages of design. However, the generation of architecture within an environment, which already includes structural principles, may bring us one step closer to this transition of virtual to physical by including gravity in architectural generation while not diminishing the creative form-generating process. An approach has been proposed which responds with a concept of ‘heavy design’. This type of approach incorporates logics from other disciplines, primarily structural engineering, to inform design. The design process incorporates the structural behavior of a system into the architectural model. Engineering offers a mathematical interpretation of the physical world and this is inherently suited to algorithmic design because it is already in equation form. It can thus be programmed into the architectural form generational software. The variables used in the equations become the variables within the architectural design and this inherently brings the natural physical laws to the architecture through a numerical, algorithmic method. The design produced is not a singular answer but rather a responsive vocabulary of a structural system, which is then employed in design in differing conditions. The architecture produced is both function and ornament, having cultural interpretation but carrying out many engineering tasks: a true parametric architecture.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.157 | 0.045 |
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".