Analyzing the Economic Benefit of Woodland Caribou Conservation in Alberta
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
This thesis seeks to measure the economic benefits of Woodland Caribou conservation in Alberta, Canada. Woodland Caribou are listed as threatened (Environment Canada 2008) both federally and provincially. Stated preference techniques were used to elicit the public’s willingness to pay for caribou conservation using the contingent valuation technique and a form of attribute based choice. Data were collected using a central facility method, audience response systems and the ballot box technique in various locations across Alberta. Conditional logit and random parameters logit models were estimated for both valuation formats individually as well as jointly. A range of benefit estimates were developed. These benefit data were then compared with cost data (Schneider et al. 2010) to examine the economically efficient level of caribou conservation. This study develops economic value measures in the context of both legislation and the comparison of valuation approaches.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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