Analysis and Economic Valuation of Off Highway Vehicle Use in Southwestern Alberta, Canada
Bibliographic record
Abstract
Outdoor recreation is an important and yet often undervalued land use. Measurement of the economic value of outdoor recreation, assessment of the impacts of land uses on these values, and incorporation of this information into land use decisions can be useful in assessing land use tradeoffs. This research used a travel cost approach to investigate the characteristics and staging area preferences of off-highway vehicle (OHV) riders, and the economic impacts of logging on OHV riders, near the Crowsnest Pass area of southwestern Alberta. OHVs in this study included dirt-bikes, all terrain vehicles, side-by-sides, and highway vehicles that are driven off-highway. Information about the trip frequency and location of OHV riders, in addition to demographic, socio-economic, and land use preference and value information was collected through both an onsite survey and a follow-up survey. A random effects negative binomial count model was used to estimate a consumer surplus value for an average OHV trip of $258. This value was robust to a variety of sensitivity analyses. The total benefit of OHV riding in the area to OHV riders over the summer and fall months is estimated at $2.8 million dollars. In addition, the results of a stated preference component of the count model show that local OHV riders do not feel crowded in the area. Many more OHV riders could start to use the area before a sense of congestion would cause OHV riders to reduce the number of trips they take to the area. A random utility model (RUM) of staging area choices of OHV riders was also estimated. Riders were significantly affected by the travel cost, total length of OHV trails nearby, and the range of elevation that can be travelled using the nearby trails. No measured variables that were related to the logging history of the area contributed significantly to staging area choices of OHV riders. Several scenarios examining the effect of changes to the availability of nearby trail length of the examined staging areas were examined. The welfare effects of access changes to staging areas along the Highway 3 Corridor were more than five times larger than the effect of similar changes to other staging areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".