Reconfiguring Ground: Temporalities and Properties of Substance
Bibliographic record
Abstract
This article explores the interplay between essential and accidental properties of substance as social and environmental interactions within the evolving urban landscape of Amsterdam’s Nieuw-West. Tracing these transformations from peat bog to polder, through the 1930s Extension Plan, its mid-20th-century construction, and its present-day form, the article examines how land construction and inhabitation shape environmental and human histories, written through geological, ecological, built, and social taskspaces. Each iteration of figure-ground reconfigures relationships, influencing the intersecting and symbiotic actions of taskspaces and urban/natural processes. Drawing on Aristotle’s metaphysics, Ingold’s deep surface, and the temporality of landscape, this article examines how taskspaces—embodied actions of habitation (urbanization, wear, maintenance, adaptation) and environmental processes (weather, ecology, soil)—function as symbiotic relational forces affecting the climate, situating locally our planetary condition. These interactions reside within the dynamic tension between process and substance, where material formations and social structures emerge through time. It traces Nieuw-West’s foundations from reclamation and extraction to its hybrid formation as a garden city and modernist suburban structure, highlighting the ongoing tensions between social and ecological displacement. By grounding the epistemology of substance, the article reveals narratives of fragmentation—both ecological and social—embedded in urban development. Critiquing the ongoing urban densification that extends Nieuw-West’s early commodification and imposed efficiencies, the article instead advocates for a dynamic approach—one that reconnects built and natural environments through collective social practices. By reimagining social contracts as continuums of care and ownership, it highlights the terrestrial, strengthening relationships that reactivate collective environmental imagination, bridging ecological and social disconnections, and enhancing both resilience and agency.
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 | 0.039 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".