Bibliographic record
Abstract
This research on the benefits of increased wilderness preservation has entailed the development of contingent valuation surveys to elicit consumer’s WTP for the province of British Columbia. The study came about after the Protected Areas Strategy (PAS) proposed an additional 6% of B.C.’s land base be set aside for protection. Two surveys were used, one survey was distributed province-wide, while the other was issued to third and fourth year university students in both land use and forestry economics. A dichotomous choice format was chosen as the most appropriate approach due to its simplistic nature and its success in previous studies. Similarly, a logistic model was applied to calculate the probability of a person agreeing to pay to a pre-determined offer amount. The results of the province-wide survey indicated that respondents valued additional wilderness protection in British Columbia at $371.34 per household per year. Aggregating this amount to include all B.C. households yielded a value of $484 million per year. The results of the classroom survey showed that the respondent’s WTP was $326 per year for a total of $716 million when aggregated for the whole adult population in B.C. The differnce between WTP values between surveys is partly due to the fact that the WTP for the classroom survey is on a per person basis while the estimated WTP for the provincial survey is on a per household basis. Similarly, the province-wide survey included individuals of all educational backgrounds while the classroom survey included only individuals with post secondary education. Finally, while the Government of B.C. has decided to increase the level of wilderness protection to 12 percent, the average desired level of protection for both surveys used in this paper was 10.75 percent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".