Commercialization Decisions and the Economics of Introduction
Bibliographic record
Abstract
A Commercial horticultural industry that establishes plant-breeding nurseries for an exotic species throughout a regional economy will expand until the marginal profit of the last nursery established is zero. However, a regional government concerned with social welfare will take into account not only the profits of the horticultural industry but also any expected costs of an accidental invasion. The latter costs will consist of the discounted expected social damages due to an increase in the rate of invasion over time and the increase in expected damage cost per hectare caused by an additional nursery. A government can employ an introducer' equal to the latter social costs to ensure that the plant breeding industry establishes the optimal number of nurseries. We illustrate this outcome with the example of purple loosestrife (Lythrum salicaria) in North America. In the absence of any tax, the horticultural industry will establish n-3528 nursery operations, and the expected damage from invasion is US$ 28.2 million per year. With the tax, only n = 300 nurseries are established but the expected damages from invasion are reduced to US$ 1.3 million per year. Although profits for the horticultural industry are lower from the tax, the net gains in overall social welfare more than offset the losses. Although these results are illustrative only, they show that the problem of plant invasives initiated by commercial operations is amenable to standard economic analysis and solutions, such as implementation of an introducers' pay tax
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How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".