Work hard, play hard: selling Kelowna, BC, as year‐round playground
Bibliographic record
Abstract
A keen interest in place making and place selling is widespread in contemporary society. While the bulk of academic research has focused on studying the restructuring of large urban conglomerates, places beyond the exploding metropolis, by comparison, have received little attention, especially when it concerns Canadian landscapes. In an attempt to study the particularities of place making in contemporary smaller, more isolated communities—hinterlands—this work analyses the city of Kelowna, in British Columbia, Canada. We argue that historically Kelowna, a small rural community specialising in ranching, forestry and fruit production, since the early 1980s, has been re‐imagined and re‐designed, on the one hand as an all‐year playground and as an innovative frontier for high‐tech industries; on the other hand, this post‐Fordist reinvention contains a discourse of ‘whiteness’, one that entices by packaging ‘place’ in terms of ‘sameness’ and ‘familiarity’. In contrast to large cosmopolitan post‐industrial cities, hinterland‐type cities are invented, sought and lived as geographies cleared from the ‘elements’ that make cities ‘unsafe’.
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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 | 0.000 | 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 | 0.015 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".