Bibliographic record
Abstract
Cet article explore la culture musicale des mineurs de Kirkland Lake et en examine l’une de ses dimensions, celle exprimee par leurs pratiques de la musique, qu’elle soit symphonique ou populaire, chantee ou instrumentale, qu’elle se traduise par un concert ou qu’elle accompagne la danse ou les defiles. Connaissant les noms et les occupations de tout le personnel de deux des principales societes minieres de la ville, la Lake Shore et la Wright-Hargreaves Gold Mines, nous avons cherche a savoir si les mineurs etaient relies, d’une maniere ou d’une autre, aux differentes manifestations musicales rapportees dans le journal local, le Northern News , tout au long de l’annee 1934. Selon nous, la diversite des pratiques musicales observee s’expliquerait d’abord par la presence de nombreuses communautes ethniques parmi les mineurs mais aussi par des conditions de travail fort differentes, selon que le mineur travaille sous terre ou au jour. Abstract: This article explores the musical culture of Kirkland Lake miners and considers one of its dimensions, as expressed by their musical practices, whether classical or pop, vocal or instrumental, performed at concerts or accompanying dances or parades. With access to the names and occupations of all the employees of two of the major mining companies in the city, Lake Shore and Wright-Hargreaves Gold Mines, we sought to determine if the miners were linked in one way or another to the different music events reported in the local paper, the Northern News , over the year of 1934. In our view, the diversity of musical practices observed could be explained by the presence of many ethnic communities in the mining workforce, and also by widely different working conditions, depending on whether a miner worked underground or at the surface.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".