Mapping as a Complementary Perspective on the Dynamics of Participation in a City’s Musical Life
Bibliographic record
Abstract
Maps and map-making have been used in a range of research about musical phenomena in cities. Yet, most of these studies focus on musicians; few have attempted to understand how people take part in a city’s musical life in terms of event attendance. Likewise, little has been said about the attendance habits of immigrants, despite the quick transformation of urban populations due to the expansion of human migration. Approaching a subject that has received so little attention as the dynamics of participation of immigrants in a city’s musical life therefore requires an inventive research design. Building from a methodology combining semi-structured interviews and observation, I used maps and map-making to deepen the analysis of North African immigrants’ cultural practices in Montreal. Trying to give a spatial legibility to their musical activities in the city generated many technical and theoretical concerns, but was also helpful for reflecting on the project differently and highlighting some characteristics of the data that were not obvious from the initial fieldwork. In brief, maps and map-making proved to be efficient complementary tools to ethnography, bringing new insights and raising new queries about the practices being considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.110 | 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 teacher head, 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".