Bibliographic record
Abstract
Canada sits on a perilous edge amidst outcries of potential exponential environmental disasters. This is not a thesis for fashion, it is a thesis for survival: Lytton Samsara is a response to climate change in 2021. The emergence of Climate Change and its effect on the built environment is the most important issue of the 21st Century and in 2021 British Columbia, saw a substantial increase in environmental disasters. Record breaking heatwaves developed to large wildfires that destroyed large landscapes and small towns. Canadian must look to architecture to preserve British Columbian towns, and livelihoods. We must evaluate the realistic outcomes of forest fires and other environmental disasters by accepting their destructive nature and designing economically innovative structures. Climate change and natural disasters seem to be going hand in hand. This past year British Columbia experienced record-breaking heat and drought which lead to an unparalleled forest fire season. Fire destroyed the town of Lytton BC displacing all its residents and evacuating them hundreds of miles away to other cities with hotel rooms to house them. The unprecedented hot, dry summer was followed by torrential rains and floods that ripped apart essential highways and destroyed towns. The entire town of Merritt was evacuated to the same places where Lytton evacuees were still living. Destruction of small towns in BC is becoming all too commonplace. This calls into question our western values as buildings as permanent structures. The Shinto Shrines at Ise Jingu offer a different ideology on buildings as dynamic and impermanent. I offer here an alternate way to view post-disaster rebuilding and a proposition for bringing people back into the community. This project recognizes the Nlaka’pamux band, the Lytton First Nation is located on 14,161 acres of land divided into 56 reserves. The reserves are located at the site of the Indian Village of Kumsheen.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.379 | 0.072 |
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".