Breathing Walls, Envelopes and Screens for Cross- \nSpecies co-living adaptation of built environment: The bio-climatic layers in systemic approach to architectural performance
Bibliographic record
Abstract
The paper suggests a possible systemic interaction with built environment that is to lead towards its transition to Post-Anthropocene through cross-species co-living oriented governance. Today, governments across the world, such as Czechia, UK, Norway, Turkey, Canada or US are releasing strategies and programs for climate adaptations, discussing weather, biodiversity and food security (Czech Republic Ministry of the Environment & Czech Hydrometeorological Institute, 2015; Department for Environment Food & Rural Affairs (DEFRA), 2018; Flæte et al., 2010; Republic of Turkey Ministry of Environment and Urbanization, 2012; Richardson, 2010; U.S.Department of State, 2014). The paper exemplifies and seeks for systemic relations and reflections of gathered documentation of breathing walls, envelopes and screens that are generating bio-climatic layers in built environment. The diverse study journeys samples that were co-designed through vernacular culture and the author’s own research by design speculations are investigated and speculated upon through gigamapping. Gigamaps are devices for design inquiry rather than analytical tools like those used in systems engineering or in hard systems models (Sevaldson, 2018). Accordingly, this Gigamapping is not to present any hard data model but to inform and speculate on the investigated field that is grounded in research by design on cross-species co-living in built up environment through possible architectures and architectural and urban design parasites transitioning towards synergetic landscapes of our envisioned futures.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".