Urban Choreographics: Tracing the Extralinguistic Pedagogies of Montreal’s Underground Metro System
Bibliographic record
Abstract
In North American cityscapes commuters must perform a specific set of gestures in order to efficiently move through and around public architectural spaces. The mass adoption of these gestures represents a form of extra-institutional learning facilitated by the choreographic characteristics of everyday architectural spaces. The urbanite’s quotidian movement through the built environment may then inform their understanding of what normative movement looks and feels like. The purpose of this research-creation thesis is to investigate how adult human cognition and epistemic formation is affected by bodily movement through contemporary urban architectural spaces. Locally there are few spaces where the procedural nature of city architecture is felt more than when using the underground public transportation network. For this reason, the Société de Transport de Montréal’s (STM’s) subterranean metro stations are the focal site of this inquiry. Using ethnographic (experimental field recordings and naturalistic observation) and arts-based methods (inconspicuous public performance and long-exposure film photography) this performance ethnography identified and analyzed recurrent patterns and rhythmic structures of Montreal’s underground architectures which cause these spaces to be propulsive for some and disabling for others. The findings of this qualitative study emphasized the hypervisibility of those whose bodies are dissociated from the rhythms of “normative” movement in these spaces. Though further studies are needed to draw a causal relationship between human cognition and the public spaces they inhabit, this thesis demonstrates the potential of arts-based research to create an output which mediates metric measurement and one’s embodied experiences of space for the purposes of research and critical reflection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".