Expanding the Notion of Care in Architecture: Recovering a more-than-human Third Landscape in Kyoto
Bibliographic record
Abstract
Drawing on de la Bellacasa’s Matters of Care: Speculative Ethics in More than Human Worlds (2017), this research-design project aims to expand the conceptual framework of care in architecture by incorporating the agency of non-human entities (Fitz and Krasny, 2019). With the declining Satoyama landscape in Kyoto—an agricultural landscape in Japan historically shaped by care—a physical context featuring sika deer, secondary Satoyama woodlands, and Kyomachiya (traditional townhouse in Kyoto). Local remaining residents are reconceptualised as a neglected more-than-human assemblage—a Third Landscape that calls for care. The presentation, articulated in the form of a picture book, traces the life cycle of a structural column from a Kyomachiya, adopting an animistic perspective—that of the column itself. Within this framework, care is defined as the ability to both receive and provide material, social, and ecological conditions that allow the vast majority of humans and other-than-human entities to thrive. Examining the column in its various states, as Japanese cypress, structural components, and decomposed timber, the study reveals the complex interplay of receiving and giving care that includes the Satoyama woodlands, the deer, the inhabitants of Kyomachiya, and future generations of cypress trees. Within a broader context, the picture book narrates a landscape recovery design project, envisioning the systematic dismantling of abandoned residential structures, thereby contributing to the restoration and reinvigoration of the natural landscape. This presentation is part of the Ecopoetic Formations for Transgenerational Collaboration scheme, which pairs four junior designers with four senior members of the American Society for Cybernetics.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".