Adaptational Strategies and the Professional Development of Cuban Musicians in Toronto
Bibliographic record
Abstract
Cuban musicians who live in Toronto face difficulties that affect their professional development. Some of them continue their careers without interruptions while others struggle significantly. What are the extra-musical factors that contribute to the career satisfaction of Cuban musicians in Canada? What are some structural constraints they experience in seeking career satisfaction? Among the range of personal attributes musicians bring to their work, some of the skills grouped under the framework of emotional intelligence (EI) nurture personal agency Consequently, I hypothesize that EI competencies, reinterpreted as additional non-musical skills, alongside social action at the institutional level, could help Cuban migrant musicians to remain employed within the Canadian creative industry. I am guided by two research questions: Could the ability of Cuban musicians to adapt to Toronto’s musical scene be related to their own social awareness of context and structural constrains and their capacity for relationship management? Do Cuban musicians experience more satisfaction in their professional development when they are more self-aware and more self-regulated? Twelve Cuban musicians shared their experiences through interviews and self-reported questionnaires. I argue in this dissertation that the presence of additional non-musical skills can help musicians feel more satisfied with their careers. Through the questionnaire, interviews, and other sources, I explore how musicians face challenges of working in a new country. How do musicians alleviate tensions while working with local musicians, performing job searches, or interacting with Canadian audiences and employers? Framed within the intersection of social psychology, music sociology, and cultural studies, this multidisciplinary study helps to understand the complexities of the adaptation of Cuban migrant musicians to a host culture. As far as I know, this perspective has not been explored before in the literature on migrant musicians in Canada.
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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 | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".