Bibliographic record
Abstract
I write this as the fiftieth day of Easter beckons and fondly recaU OUvier Messiaen's invocations of songbirds in his Messe de Pentcote for organ. Messiaen famously involved birds in many of his compositions. Another composer who regularly does this is Canada's R. Murray Schafer. Schafer's works are often created for outdoor performances in which singers and players of a wide variety of instruments interact with the environment. In works such as The Princess of the Stars, The Spirit Garden, or those within the coUection of pieces in Wolf Music (scores are available through Arcana Editions) Schafer has composed melodies for such conventional instruments as flute, piccolo, and trumpet, as weU as for voice, many of which are based on commonly heard bird songs of tiie boreal forest. When these pieces are played in their intended location and time - that is, not a concert haU at 8:00 PM, but rather in an outdoor space Uke a forest or beside a lake, and at times of day Uke pre-dawn or dusk, when the birds are most audible - fascinating things happen. Then Schafer's music becomes a polyphonic interaction of instruments and birds. What occurs is a chamber music performance with the Earth and her creatures - a trio sonata with co-dependencies of echo, wind, silence, air temperature, atmospheric pressures. Human beings control very Uttie in such a performance when they enter into the humility referred to by BiU WaUace (see Hymn Interpretation in this issue). In performance of such pieces as the for Two Voices (see ex. 1) from Wolf Music, the singers or players are often joined by the very bird whose song is captured in Schafer's composed score, adding a tiiird, fourth, or fifth dimension to die experience. It is an exciting and thrilling thing to hear a wild animal respond to one's singing. The first time this happened to me I completely altered my intended song in order to absorb and reflect my duet partner. Listening once to a soprano and clarinetist playing the Aubade of example 1, I heard their gleeful giggles as the bird seemed to insist on a different tempo than tiiey had initiated. The bird wanted it sUghtiy slower and won! And so, when humans are humble enough both to hear and to Usten, and then to learn and to be led, we can indeed find new dimensions in the world of sound. Congregational singing can have that codependent chamber music quaUty - voices uniting, ears Ustening wide, breath feeding breath - when we let it. So let us be inspired by birds. …
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.037 | 0.012 |
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".