The State of the Great Outdoors: Charting Recent Trends, Assessing Funding Needs, and Understanding Americans’ Connection to Nature
Bibliographic record
Abstract
In 2008 and 2009, the Outdoor Resources Review Group (ORRG), a private bipartisan panel of recreation professionals, public officials, and conservation advocates, assessed priorities, challenges, and opportunities in managing the nation's land and water resources. The 17-member panel, with U.S. Senators Lamar Alexander (R-TN) and Jeff Bingaman (D-NM) as honorary co-chairs, held a series of public meetings and focused workshops that culminated in a report presented to the Secretary of the Interior. In support of the ORRG effort, my colleagues and I at Resources for the Future conducted an independent assessment of trends in demand and supply of open space, parks, and public lands-as well as funding and financing of these resources-during the past quarter-century. I Our research revealed 2 especially important findings. First, there has been a marked shift from public funding of national parks and other publicly owned lands to private sector funding, largely through conservation land trusts, and to public funding of conservation easements on private land. In addition, the focus 25 years ago was on parks and recreation lands, but emphasis has shifted toward wildlife habitat, farmland, wetlands, and other kinds of open space. Second, the picture revealed through data on Americans' time spent outdoors, park visits, participation in recreation activities, and other information is a puzzling one that suggests a need for more research. Voters routinely support conservation financing referenda at very high rates and polls often show high support for parks and open space, yet the average American spends fewer than 2 hours per week in outdoor pursuits.
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 | 0.001 | 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".