Grown, Sewn, Blown, Hewn, Dwellings for New Extremes
Bibliographic record
Abstract
The International Space Station (ISS), traveling at 28,000 kilometers per hour, is an unlikely example of a dwelling on the move. Drawing on a research framework that views outerspace and Earth as a single cosmic continuum, City As A Spaceship (CAAS) introduces the concept of habitats in environmental extremes, such as space, as a metaphor for today’s urban dwelling issues. Cities must be sustainable and resilient, navigating shared conditions like density, confined spaces, complex infrastructure, resource recycling, energy efficiency, digital connectivity, and the implications of geopolitical instability. This submission focuses on “cities on the edge” – those situated at the intersection of land, water, and atmosphere. Roughly 5 billion people live within 400 km of a coastline and below 800 meters above sea level, in regions particularly vulnerable as climate change accelerates rising sea levels and impacts access to essential resources. Building on Folke and colleagues’ resilience framework (2016), we emphasize the importance of design that not only ensures habitability but also supports adaptiveness. CAAS’ approach focuses on three design principles: scale, impermanence/decoupling, and transportability and draws insights through case studies; including the ISS and terrestrial analogue habitat projects. By balancing technology, environment, and the social, these are examples of multimodal resilience via strategies we term “grown, sewn, blown, and hewn”.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".