Bibliographic record
Abstract
Gentrification involves the transition of inner-city neighbourhoods from a status of relative poverty and limited property investment to a state of commodification and reinvestment. This paper reconsiders the role of artists as agents, and aestheticisation as a process, in contributing to gentrification, an argument illustrated with empirical data from Toronto, Montreal and Vancouver. Because some poverty neighbourhoods may be candidates for occupation by artists, who value their afford ability and mundane, off-centre status, the study also considers the movement of districts from a position of high cultural capital and low economic capital to a position of steadily rising economic capital. The paper makes extensive use of Bourdieu's conceptualisation of the field of cultural production, including his discussion of the uneasy relations of economic and cultural capitals, the power of the aesthetic disposition to valorise the mundane and the appropriation of cultural capital by market forces. Bourdieu's thinking is extended to the field of gentrification in an account that interprets the enhanced valuation of cultural capital since the 1960s, encouraging spatial proximity by other professionals to the inner-city habitus of the artist. This approach offers some reconciliation to theoretical debates in the gentrification literature about the roles of structure and agency and economic and cultural explanations. It also casts a more critical historical perspective on current writing lauding the rise of the cultural economy and the creative city.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.062 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".