Visitor management policy of national parks, national wildlife areas and refuges in Canada and the united states: A policy analysis of public documents
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
Abstract The published visitor management policies of national parks, national wildlife areas and refuges in Canada and the United States are important components of the overall management system. This paper analyses how the visitor management policies that apply to all units operated by each agency compare to each other and compare to an ideal framework, using data from publicly‐available sources. Analysis was undertaken by policy comparison of all publicly‐available documents available in the Canadian inter‐university library system and the internet. The quantity and quality of visitor management policy is higher with higher funding levels, as demonstrated by the US National Park Service at the high end of the spectrum, and the Canadian Wildlife Service at the low end. The US National Park Service has the most comprehensive visitor management policy, and this policy is well coordinated in one overall document. The Canadian Wildlife Service has a very weak visitor management policy structure that lacks even basic goals for visitor management. Some visitor policy gaps exist for each agency. All agencies lack explicit policies governing visitor length of stay, human resources required for visitor management and economic impact measurement. This is the first policy analysis of this type undertaken. It provides a basis for the revision and improvement of these policies in the future.
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.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it