Sonic City: an exhibition of photography, A/V installation, community action
Bibliographic record
Abstract
By taking participatory action research, utilizing sound as a means of harnessing the socio-cultural, and documentary exhibiting as mimesis, this paper takes themes of contemporary underground dance music culture, sonics, political engagement, and human development in urban spaces and looks at the key processes involved in formulating my documentary project Sonic City throughout the years 2014-2016. From personal experiences in Berlin (GER), London (UK), and Toronto (CAN) to research on the ephemeral nature of what creates thriving underground dance music scenes, this paper proposes that discotheques are vital and underestimated spaces for urban development, where complex socio-cultural monads of production and consumption are exercised and actualized. Sonic City as a documentary project is meant to shed light onto the places, spaces, and people involved in this vibrant culture, while as an artistic endeavour is attempting to put relational aesthetics at the forefront of documentary exhibiting, blurring the lines between gallery expectations and dance space experience.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 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".