Bibliographic record
Abstract
Abstract This chapter considers how film sound can become an essential part of soundscape research conducted by acoustic ecology, and how folding the discourse of film sound theory back onto acoustic ecology can correct for a variety of gaps in the field’s foundational texts. The chapter focuses on media produced in the city of Vancouver, birthplace of acoustic ecology and longest running case study of the World Soundscape Project, as an example of how the sonic environment of a specific geographical locale can be researched through film and audiovisual media. The author uses the sound of trains as represented in Vancouver-based films as the foundation for addressing how sound is tied to geographical specificity in local media: given that the sounds of trains have become a defining characteristic of the city, we can say that the entire city becomes the acoustic profile across which these sounds can be heard. The work of acoustic profiling in this chapter engages with the emerging practice of unsettled listening, whereby listener positionality is taken into account when trying to understand the relationship between sound and culture within a given acoustic profile. This analysis demonstrates why film sound design should be an important area of consideration for soundscape research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".