Seeing the Wood & the Trees
Bibliographic record
Abstract
This thesis posits an architectural use case for oft-discarded parts of hardwood city trees, in turn implying a new mode of reciprocal care for the urban canopy. By exploring the ecological underpinnings of tree physiognomy within the context of the City of Vancouver, in combination with experiments in craft and non-destructive structural testing, this project aims to uncover a design process suited to the indeterminacy of heterogeneous, anisotropic materials. As it stands, the City of Vancouver, along with the rest of British Columbia, takes its trees for granted. As climate change continues unabated, our forests, both rural and urban, continue to be planted and tended using outdated models of growth and resilience, creating biodiversity deserts ill-equipped for the environmental fluctuations predicted for the coming century. Additionally, despite being hailed as “the material of the 21st century,” wood is often used by architects as one-to-one stand in for concrete and steel, a process that denies the complexities and inherent qualities that give trees their strength and resilience. In doing this, architects risk depleting the very resource we depend on to adapt to, and possibly combat, the climatic changes that threaten the delicate balance required for human and non-human life. If we are to have any chance of reaching symbiosis in this current paradigm, we must leave more diverse forests intact, while learning to use trees and wood in all manners of eccentric and efficient ways. To start this process, this project focus on the material lifecycle of urban trees, and the waste streams they create. These materials, while exhibiting great structural strength with low embodied carbon, are difficult to mill and thus utilize in a typical design process. In order to re-valorize the inherent form of hardwood trees, an approach is required that entwines craft knowledge from the past with tools of close observation enabled by contemporary technologies, so that design intent is matched with available materials. The result is the development of a design process that is neither materially exclusionary, nor obsessively controlled, but rather a process that oscillates between the scale of the detail and the scale of the territory. In short, it allows us to see the wood & the trees.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".