MétaCan
Menu
Back to cohort
Record W4410945705 · doi:10.25071/1708-6701.40508

A Locational Study of R. Murray Schafer’s Music for Wilderness Lake [1979]

2025· article· en· W4410945705 on OpenAlexvenueaboutno aff
Sarah Teetsel

Bibliographic record

VenueCAML Review / Revue de l ACBM · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsWildernessGeographyArtEcologyBiology

Abstract

fetched live from OpenAlex

Music for Wilderness Lake [1979] was a pioneering composition in the development of Canadian composer R. Murray Schafer’s (1933–2021) environmental works. Envisioned as a performance for twelve trombones gathered around Southern Ontario’s O’Grady Lake, it continuously evolved as the realities of the outdoor location shaped the compositional process and the premiere performance. Schafer was prompted to think about how an outdoor, rural location affects musical performances and what concessions it required. Despite the significant role Music for Wilderness Lake played in Schafer’s compositional output, it is too often scripted as a first step to his later environmental works. In this article, the author recontextualizes Music for Wilderness Lake by exploring the experimentation that took place as Schafer’s vision was adapted to performance and logistical challenges. One of the unique features of Music for Wilderness Lake is the use of a central raft on a lake, from which Schafer cued the full ensemble during the premiere. By examining the performance site, this article highlights how some of the aspects of the location that Schafer found exciting—wide spatialization of performing forces and lively echoes—affected the development of Music for Wilderness Lake. Using contemporaneous articles (Littler 1979, MacMillan 1979, and Sweete 1980); interviews (including Westerkamp 1981); sketches of the location; and the film made of the performance (Music for Wilderness Lake, 1980, Fichman-Sweete Productions); this article explores why O’Grady Lake was chosen for the premiere and how the space helped develop specific relationships among participants based on spatialization and instrumental groupings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.271
Threshold uncertainty score0.539

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0360.011
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.016
GPT teacher head0.255
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueCAML Review / Revue de l ACBMSame topicAmerican Environmental and Regional HistoryFrench-language works237,207