<i>Pulp</i> ‐ Studio‐Based Research in Thin‐Shell Cast Paper Structures
Bibliographic record
Abstract
This paper reflects upon a sequence of seven research studios, taught within a six-year timespan in three different architecture schools, in which we developed approaches to casting thin-shell (monocoque) paper structures at full scale. Processes of material selection and material harvesting/processing, formwork design and fabrication all informed the formal expression of the shells. In the context of architectural education, fabricating at full-scale can make structural principles accessible, but large constructions can be expensive for students, and can also create unnecessary material waste. This sequence of studios, called PULP, allowed students to fabricate spatial structures at full-scale using materials available at little to no cost. The large structures have the potential to biodegrade completely, creating no landfill waste, and no adverse impact in their final resting place. The dearth of research or precedents in cast‐paper‐as‐structure offers a unique opportunity for novel, basic or “blue skies” research in this area. Processual knowledge gained through leading this studio‐based research over several years has allowed us to focus more recent research on scaling-up and using material combinations and fabrication techniques that are simple and effective. The increasingly focused investigations and larger scale of the paper cast structures in the most recent (last two years of) studio research suggests that there is something like a paper-specific formal vocabulary in thin shell structures.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".