Bibliographic record
Abstract
Management of urban Canada geese impacts can be assisted by the use of economic analyses of both the problem and the proposed solution. Management of a species that is both geographically mobile and stationary, protected by the Migratory Bird Act of 1918, and loved by much of the public while posing a significant risk of damage to both private and public property is a difficult task. The issue is further complicated by the scope and scale of urban goose impacts. While the presence of urban Canada geese results in both positive and negative impacts, this paper will focus primarily on the management problems involving overabundance and concentrated populations. The many negative impacts caused by Canada geese may occur at a “lawn” level, or be aggregated into a “community” level. Management actions that solely focus on the “lawn” level may shift the problem to other parts of the community. Economic analysis provides a venue for management strategies, either individually or in aggregate, to be evaluated in a common time frame that accounts for their real costs and resulting benefits. Three economic techniques can be used to evaluate management strategies at any geographic level: economic feasibility, economic efficiency, and cost-effectiveness analysis.
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 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) | 0.003 | 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 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".