Bibliographic record
Abstract
As visitors first step into the latest exhibition at the Canadian Centre for Architecture (CCA), the senses are immediately aroused. We are drawn through a dark and narrow tunnel and, before our eyes can adjust, the sounds of a railway station, with trains pulling up to and leaving platforms and announcers calling out the next departures in various languages, immediately evoke the constant movement of city life. A small screen tells us that one minute we are in Cologne, the next in Lille, and thus, with eyes squinting and ears alert, begins a sensorial voyage through urban space. Questioning assumptions is the primary objective of "Sense of the City," curated by the CCA’s recently appointed director, architect, and scholar Mirko Zardini, who wants to inspire visitors to think differently about how they experience their urban environment. Zardini reminds us that although the visual has always been privileged in urban dwellers’ conception, design, and interaction with their milieu, cities also stimulate the other senses in a multitude of ways. A more pronounced appreciation of how we touch, hear, smell, and perhaps even taste the city, argues this exhibition, will not only lead us to a fuller, more balanced understanding of our habitat, but will also encourage us to formulate new claims for an environment planned with greater sensitivity to our fundamentally, though oft-neglected, corporeal relationship with urban space.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".