Bibliographic record
Abstract
This project tells the story, hour-by-hour, of a night out at a techno rave in Tiohtià:ke (Montréal). It starts with us at 9:30pm the night of and follows us, staying up through the night until the sunrise, and riding home with a feeling of something. The aim of this project is to retain the feeling of lostness that a loud room and a sea of—chemical, organic, energetic—bodies impart. In recounting the various encounters, starts, transfers, that made up the night, it explores the circulation of affect through and around the dance floor. What happens in a dark, loud, crowded room, when experience meets its fringes? Where does the self go when it joins the community? Inspired by Kathleen Stewart’s attention to the circulation of public feelings, motions, shock, banalities, the ‘ordinary affects’ which constitute a life on a personal and collective level, I trace the night through moments, both brief and durational, which point to something else. Working through a Deleuzian framework for affect, I account for the bodily, rhythmic, and interpersonal resonances that make up an affective environment. The collaborative elements of the underground music scene mirror the unity of bodies in synchronous motion. The processes of attunement between dancers and DJs are models for an alternate mode of being in relation. From dancefloor ethics to dancefloor, from dancefloor to organising practice, the project traces the ‘affective anatomy’ of a night out and imagines new social arrangements beyond the limitations of discrete selfhood.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.024 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".