A Conversation About Urban Choreography — with Justine A. Chambers, Alana Gerecke & Annabel Vaughan
Bibliographic record
Abstract
This episode of Below the Radar is a special live event recording from “A Conversation About Urban Choreography,” presented in-person at SFU’s Vancouver campus on November 9, 2021.\nTaking gesture as a point of entry, Justine A. Chambers and Alana Gerecke extend their collaborative exploration of the everyday choreographies that are built into an urban experience. Combining artistic and academic research, they index the various bodily orientations cultivated by the built and social structures that shape everyday spaces. By tracking an archive of everyday gestures that are prompted by various components of built and social space, they insist on the lasting and vital information contained within those specific organizations of moving bodies. They emphasize the significance of embodied knowledge—even, or especially, as it lives in invisibilized daily gestures. \nIn this discussion, Chambers and Gerecke are joined by architect Annabel Vaughan. Together, the panelists explore the accumulation of living archival gestures generated by the interactions between moving bodies and built space, an evolving assembly of lost gestures. This public conversation was presented with the aim of sharing evolving research by inviting those present to engage in a consideration of the embodied details of urban circulation.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".