Sense of place on the periphery: Exploring the spatial practices of the creative class in St. John’s, Newfoundland and Labrador
Bibliographic record
Abstract
Urban and regional spaces in the early 21st century have been dramatically reshaped by economic performances linked to innovation, knowledge and creativity. Professionals in these sectors, often referred to as the “Creative Class”, are the focus of growing scholarship across the social sciences. Urban geographers, in particular have scrutinized this complex labour category and increasingly question the core spatialities of the concept, including raising awareness of the creative class in rural and peripheral spaces. In this paper, we explore the spatial practices carried out by the creative class in St. John’s, Newfoundland and Labrador—an important yet peripheral urban hub in Atlantic Canada. Drawing upon the findings of interviews with local stakeholders from municipal government; innovation, knowledge and creative industries; and the R&D sector, our analysis points to the existence of a complex and creative “sense of place” that simultaneously envisions a favourable environment for innovation and creativity but that also consistently impedes talent attraction (and retention) from outside the province. Given this context, we highlight two central issues: (i) the proximity to the Atlantic Ocean as an economic and cultural determinant of a “sense of place”; and (ii) the appropriation of this “sense of place” as a spatial practice of the local creative class fed by social and symbolic distinction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".