"The Beginning After the End" : independent music, Canadian cultural policy and the Montreal indie music scene
Bibliographic record
Abstract
This thesis is a political economic analysis of the structures of the global music industry and the place of the independent music industry within it. The objective of this study is to map out and explore some of the changes that are currently transforming these industries. I focus particularly on those issues facing emerging, independent musical artists in a globalized context; including the reasons for the dominance of the industry by the "Big Four" multinational record labels; technological advancements that have led to a reduction of entry barriers for independent labels and artists; the roles cultural policies have played to help counter the dominance of the multinational record labels and the importance of musical "scenes" to the development of independent music. This study is approached from a Canadian perspective and includes a case study of the rise and international explosion of the Montreal indie music scene in 2005. Through this case study, I explore the impact of technological innovation on this scene and the ways in which Canadian cultural policies have helped support and promote independent Canadian artists, as well as examine the current relevance of these policies. Ultimately, I hope to draw broader conclusions about the shifting structures of the music industry and how independent artists can represent, maintain and grow their culture within the US-dominated global popular music industry.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.034 | 0.021 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".