“It’s only in thinking about music, and about sound, that I can be happy” (1982–83)
Bibliographic record
Abstract
In all probability Vivier arrived in Mitterrand’s France in a mood of optimism and even relief following the recent fruitless months in Montreal. A letter to the Canada Council a few weeks later thanks them for their grant “which saved me from a deep compositional crisis.” It was the third time he had left his native city for an extended period, but unlike previous times he was not traveling to terra incognita: by now he knew Paris fairly well. The most immediate problem, finding a place to live, he solved quickly. A card postmarked June 21, 1982, to Thérèse Desjardins says he has found a furnished apartment, three rooms, with phone, at 22 rue du Général-Guilhem, in the eleventh arrondissement between the avenue de la République and the boulevard Voltaire, for 2,000 francs per month (equivalent to roughly €630 today). “For the first time in my life I feel good in Paris!” The nine months that Vivier spent in Paris are documented, in what for his biographer is luxurious detail, in a collection of correspondence with Desjardins. (Her letters to him, in contrast, seem not to have survived.) There are fourteen letters and two postcards, the earliest postmarked June 21, 1982, and the last dated February 12, 1983. This has the virtue of being the most substantial collection of letters we possess from Vivier to any one single correspondent, and is a testament to the role Desjardins now played in his life, as friend and confidante. The correspondence also allows us to follow his state of mind during these months, a period of time when his life, externally, was fairly uneventful. A letter postmarked July 2 declares that he is already installed in the rue du Général-Guilhem and composing. He repeats what he had already told her last time, that this was “one of the rare times I’ve felt very good in Paris”; and thereafter he moves on to more reflective matters about music. “What is very strange musically is that the only music that can really inspire me now is my own music—and I think that’s perfectly normal.” He complains that “it’s hard here to get to know people,” also about how expensive Paris is; on the other hand, “I’ve found what I wanted: solitude and the space to think. … Soon my piano will arrive, because for composing I really need my instrument.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.016 |
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".