Bibliographic record
Abstract
Abstract This chapter examines Peter Mettler’s film Picture of Light (1994) as an exploration of what is at stake in the debates about the documentary recording practices essential to soundscape research. Mettler and his crew travel to Churchill, Manitoba, and attempt to capture the aurora borealis on film. They take an overtly reflexive strategy that foregrounds the filmmaking process while continually questioning if our experience of the lights on film could be anything like being there in person. Asking what it might mean to hear the lights, they stage the soundscape of Churchill in ways that continually challenge the limits of documentary representation while meditating upon the role of media in shaping our engagement with the world they seek to document. This chapter argues that Mettler’s use of sound calls attention to how we perform with our media as the very basis of our engagement with the world, a strategy the author calls immersive reflexivity: the foregrounding of mediality as a tool for engagement rather than distanciation. This chapter situates Mettler’s strategy within the long history of experimental film, particularly visual music, and its attempts at generating more holistic experiences through self-conscious means, particularly with respect to sound/image relationships. By framing Picture of Light through the discourses of documentary and experimental film, this chapter demonstrates how Mettler’s film teaches us to address the practice of field recording in soundscape research as highly staged material that can, nevertheless, provide faithful means of engaging with the world that presents itself to the microphones.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.028 | 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".