Visual artists: counter‐urbanites in the Canadian countryside?
Bibliographic record
Abstract
Professional visual artists have always enjoyed considerable latitude in the selection of a place of work and residence. Recent decades have witnessed their growing presence within the Canadian countryside. This paper seeks to provide an interpretation of this phenomenon by exploring two sub‐objectives. First is to determine whether artists who establish themselves in rural communities can be considered to be part of the counter‐urbanisation movement, involving the relocation of urban residents down the settlement hierarchy. Second is to identify what types of migration are occurring and why. Our surveys of visual artists residing in the southern Ontario communities of Elora and Parry Sound reveal that most participants are part of a movement involving the decision to take up both residence and employment in a rural locale. We further find that the relocation of visual artists is driven to some extent by a strong attachment to natural landscapes. By way of conclusions, we briefly speculate about the broader population of urban residents. We remind ourselves that artists often have been harbingers of new movements and that today there are growing numbers of workers outside the artistic community who also have increasing latitude in regards to choosing where to live and work. Overall, our findings suggest that there is ongoing blurring of geographic boundaries—between space and place, between place of work and place of residence and, of course, between rural and urban.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".