Bibliographic record
Abstract
In the sound documentary Listening is Action, the composer Hildegard Westerkamp engages in a conversation with Luis Velasco-Pufleau at her home in the city of Vancouver, which is situated on the traditional, ancestral, and unceded territories of the xʷməθkʷəy̓əm (Musqueam), Sḵwx̱wú7mesh (Squamish), and səlilwətaɬ (Tsleil-Waututh) Nations. She talks us through her first field recordings and her soundwalking practice, her work at the Vancouver Co-operative Radio, and her participation in the World Soundscape Project, all of which started or took place in the 1970s. Furthermore, she takes us on soundwalks at places she used to go and record more than thirty years ago, such as those now called Kitsilano Beach and Vancouver’s Downtown Eastside, and that constitute the sources for her soundscape works A Walk Through the City (1981) and Kits Beach Soundwalk (1989). This sound documentary is an invitation to listen more attentively to the multiple voices that inhabit our environments in order to imagine new, plural, and unforeseen realities. The sound work Listening is Action is enhanced by a written commentary in which Luis Velasco-Pufleau explores the radical relationality of listening and the connection between Westerkamp’s thinking with the work of Pauline Oliveros and Hannah Arendt. Finally, he engages with critical listening positionality in order to reflect on some of the limits and contradictions present in the sound documentary.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.012 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".