Search (and rescue) for the ultimate selfie: How the use of social media and smartphone technology have affected human behaviour in outdoor recreation scenarios
Bibliographic record
Abstract
The practice of outdoor recreation was historically a form of therapy and escape from the rigors of modern industrial daily work-life, and it remains a favored pastime today, with 70% of Canadians and 91% of British Columbia residents participating in “outdoor recreation or wilderness activities”. In recent years, there is a belief that the surge in popularity of hiking is due to beautiful destinations becoming more visible on social media. Further, the proximity of urban centres like Vancouver to such destinations reassures users that the safety benefits of urban technologies including smartphones, will remain accessible and reliable throughout their outdoor exploration and that help is available in the event of an emergency. This belief has led to many instances of Search and Rescue teams being activated, which would previously have been avoided by outdoor recreation participants making different choices based on their skill and experience. The culture of outdoor recreation has therefore been increasingly affected by smartphone technology in terms of users’ risk perception while recreating outdoors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".