Making meaning out of mountains : skiing, the environment and eco-politics
Bibliographic record
Abstract
This research provides a sociological analysis of skiing as a form of outdoor recreation and nature tourism in British Columbia, Canada. A qualitative multi-method approach is used, combining discourse analysis, interviews with skiers, and unobtrusive field observation at Whistler Blackcomb and Whitewater ski resorts. Through a focus on discourse, embodied interactions among humans and non-humans, and flows of power, this research describes an environmental ambiguity at the centre of skiing. There is a tension between interpretations of skiing as an environmentally-sustainable practice and notions of skiing as an environmental and social problem. Skiing is based on the symbolic consumption of nature and is understood by many participants as a way of entering into a meaningful relationship with the non-human environment. However, interpretations of skiing as a non-consumptive use of non-human nature are too simple. Social movement groups disrupt pro-environmental discourses of skiing by challenging the sport’s ecological and social legitimacy. Many skiers also articulate a self-reflexive environmental critique of their sport. In these instances, skiing is brought into the realm of politics. Recreational forms of interaction with the non-human environment tend to be at the periphery of environmental sociology. At the same time, sport sociologists tend to focus on the social dimensions of outdoor recreation, while bracketing out non-human nature. This research brings these two fields of inquiry into dialogue with each other, thereby addressing this double lacuna.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.038 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".