On estimating the option value of preserving a wilderness area
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper option pricing theory is used to analyse whether or not to preserve a wilderness area. A numerical approach is demonstrated that can be applied to any generalized stochastic process. The impact of assuming that amenity value follows a logistic process, rather than geometric Brownian motion, is considered. The calculation of critical levels for amenity value necessary to justify preserving a wilderness area such as the Killarney Provincial Park in Ontario or the Headwaters Forest in California is demonstrated. The impact of changing the assumed growth and volatility of amenity value is also examined. JEL Classifcation: D81 Q26 Ce mémoire utilise la théorie de la tarification d'une option pour analyser si on doit préserver un espace naturel. On utilise une approche numérique qui peut être appliquée à tout processus stochastique généralisé. On examine l'impact de possibilités que le profil de la valeur de la ressource dans la temps suive un processus logistique plutôt qu'un pattern géométrique de type Brownien. Le texte montre le calcul des niveaux critiques de la valeur de la ressource qui seraient nécessaires pour justifier la préservation d'une espace naturel comme le parc provincial Killarney en Ontario ou les forêts Headwaters en Californie. L'impact de postulats différents quant à la croissance et à la volatilité de la valeur de la ressource est examiné.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it