ICE RECORDS: Sonic explorations of the climate records captured in ice sheets and glaciers
Bibliographic record
Abstract
As glaciers melt and ice sheets retreat, information about the Earth’s climate histories is also vanishing as ancient air bubbles captured in ice are released. The atmospheric archive recorded by glaciers and ice sheets provides unequivocable evidence of increased greenhouse gas emissions and thus global warming. As mountain villagers abandon their remote communities due to extreme water scarcity in the Himalayas and move to cities, environmental knowledge and practices of caring for glaciers also disappears. \n \nThis “record” and vinyl pressing gathers together material from my encounters with scientists, ecologists, activists, communities, and folksingers. From field recordings captured at various glacial sites by researchers in Canada, Svalbard, Norway, and India to a Ladakhi folksong about mountains, rivers, and streams, these tracks take listeners into the sonic worlds of ice. \n \nEvery recording is a consequence of the moisture content, air pressure, and temperature that combine to modify the properties of sound waves as they travel through a medium. Glaciers too undergo mass balance changes due to temperature rise and precipitation seasonality, which accelerates melt by reducing surface albedo and increasing absorption of solar radiation by glaciers. Thus ice is modified in much the same way that sound is shaped by environmental factors. In a sense, these field recordings can tell us both something about the past -- the changing nature of glacial ice -- but they also carry more recent information about the conditions under which they were made. This includes air pressure, humidity, and notably temperature. The sounds of ice are, in effect, an acoustic archive of multiple temporalities and environmental histories. \n \nICE RECORDS is a limited-edition vinyl LP produced by BEK Centre for Electronic Arts, Bergen in Norway and pressed at Nordso, Copenhagen in Denmark.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".