Common notions and composite collaborations: Thinking with Spinoza to design urban infrastructures for human and wild cohabitants
Bibliographic record
Abstract
This paper explores the ways in which we might construct urban environments that are responsible to the needs of more than just human cohabitants. Drawing on Spinoza’s common notion and attentive to the possibilities of socio-natures that both construct and respond to the habitat needs of urban wildlife, I look at how urban design and wildlife habitat might be thought and planned together as a human/non-human composite, invoking a complex spatial and temporal choreography which serves divergent needs. Drawing on examples of urban design in Toronto, Canada, this paper offers a way to think of the city as a composite body in Spinoza’s terms, to become open to an awareness of the city as a composition of forces—a choreography of bodies that are constantly interweaving and overflowing imagined boundaries, struggles that are fought as much over time as space, the accommodation of the temporalities and spatialities of other life processes, other rhythms and cycles that would, without a recalibration, sync uneasily with the pacing and spacing of human requirements.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.039 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".