Bibliographic record
Abstract
This paper focuses on the design of buildings as part of society’s response to the climate crisis in the aftermath of the COVID-19 pandemic. It draws on a broad literature to address two interrelated goals—first, to align regenerative development and design with the necessary bottom-up adaptation strategies and human agency, and second, to identify new, broader possible roles of buildings and responsibilities of design professionals. This required a comparison of current green building and emerging regenerative approaches and identifying the relevant characteristics of top-down and bottom-up mechanisms. The paper accepts that adaptation to climate change will, to a large extent, depend on people’s day-to-day actions in the places they live, and argues that the built environment will have to be infused with the capability to enable inhabitants’ greater agency. Viewing buildings as playing a connective role in the existing urban fabric seriously challenges the primacy of the individual building as the focus of environmental strategies. The roles of building design professionals will likely expand to include mediating between top-down imposed government controls and increasing bottom-up neighborhood-scale social activism.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.039 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".