Bibliographic record
Abstract
We have a plastic waste crisis. Our waste is concealed in bins, taken out to back lanes, buried at the landfill or shipped overseas. We have become increasingly expert at physically distancing ourselves from our waste. Spaces for waste are not for humans. Waste is invisible to us. Plastic Metabolism in a Garbage Apocalypse operates within a fictional, yet plausible, garbage strike. This strike brings the global waste crisis home, registering it at the scale of a household. How do we cope? Our perceptions must shift if we are to escape the constricting infill of waste in our previously pristine domestic realms. We must see waste as a raw material. This project proposes a new system of construction, operating on the existing body of the Vancouver Special, a locally specific and common housing typology. Domestic spatial relationships are re-imagined establishing an intimate relationship between the human body and waste material and processes. Building with waste is imperative. We must see waste as an opportunity, and allow new growth through the reconstitution of waste materials. Using a playful and optimistic perspective, Plastic Metabolism in a Garbage Apocalypse allows the messy and uglier sides of human life to support a productive domestic environment.
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 | 0.012 | 0.020 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".