Un-Registered Affects; Archiving Dormant Landscapes
Bibliographic record
Abstract
“Un-registered Affects” is an experimental project in search of an alternative/meta-methodology for architectural and landscape practices of siting, based in notions of “haptic history” and “haptic geography,” that proceeds through an archiving of affective and ephemeral aspects of site derived from an embodied experience of landscape. Taking two peri-urban sites in Mississauga linked together by the Credit River, I create an alternative archive for the temporal, intangible, and fleeting narratives contained in these sites, re-presenting them as a “spatial archive” to counter notions of “the cleared site” (Burns) with a model of land as record and dwelling (Ingold), and with Indigenous ontology and knowledge that land is sacred, “alive and thinking” (Watts). I argue for a re-linking of these impermanent archives to siting practices, to reconnect the body to the layered histories of land and place. Merging distant and proximal histories, my installation places Aboriginal and ‘newcomer’ narratives into relation. The histories of the land include the death of agriculture, immigrant passage/settlement, and Anishinaabe cultivation around the Credit River. \n\tThis is an artistic exploration of tensions: between architectural/mechanical models of precision and measurement, while setting these against the poetic nature of the landscape. My installation counters architectural and colonial clearing of place as a tabula rasa by engaging in processes of surveying, sampling, preserving and archiving land, in anticipation of its imminent erasure. This project is thus a cross-disciplinary exploration of architecture, landscape, geography, and artistic practice.
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 | 0.005 |
| 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 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".