Site Surfeit: Office for Soft Architecture Makes the City Confess
Bibliographic record
Abstract
That mute paysage possesses knowledge; it sees you too. Any language that would heed these facts- that could live up to land or cityscape now, and to its contents encompassed by the presently omnipresent term - has to plot out a hearkening, not an anthropological or aesthetic seizure. That isn't simple; its tantamount to calling for a poetic, a system built out of abeyance. Within an architecture of poetry and vice versa that we could in sincerity call site-specific, sites grammar comes to occupy description, its nomenclature possesses vigilant trifling consciousness; Site peers through language to change me. Lately it makes me corporate. An index mixed by Stacy Doris, the author of Conference, archives the effluent introduction to Lisa Robertsons Occasional Work and Seven Walks from the Office for Soft Architecture under a couple of apparently nonconverging foci: I became money and return. How does this work? Rummaging back through the pink black and grey pocketbook to its counterpenetrable opener, one is pointed to these essays' genesis in the altering urban texture of Vancouver, from the sale of the Expo '86 site through the province's 2003 acquisition of the 2010 Winter Olympics. A paragraph records the premise of their authorship:
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.016 |
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".