Mindful deviation in creating a governance path towards sustainability in resort destinations
Bibliographic record
Abstract
Drawing on recent work in evolutionary economic geography, we focus on path creation as the framework for understanding how, in a resort destination context, the shift from growth models to ones based on principles of sustainability are evolving. Path creation emphasizes the power of human agency by recognizing the influence of entrepreneurs in shaping their environments. In the case study of the mountain resort of Whistler, British Columbia, we focus on one key aspect of the discourse surrounding the transition in governance from growth towards sustainability – that of affordable housing. The data are drawn from key informant interviews, participant observation and community document sources. The findings demonstrate how, through ‘mindful deviation’ from a growth model approach, Whistler entrepreneurs were able to utilize the collective agency of the community, generated in support of a new governance model based on principles of sustainability, to address the pressing need for affordable employee housing. This resulted from the opportunity to host the 2010 Winter Olympic and Paralympic Games. Through the efforts of both individual and collective human agency Whistler entrepreneurs were able to persuade the local Olympic organizing committee to conform to the resort's sustainability mandate in the development of athletes’ accommodation that would later serve as permanent resident-restricted housing. Overall, the study demonstrates the utility of employing a path creation lens as an analytical tool for understanding evolutionary change.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".