Bibliographic record
Abstract
The Great Lakes are vast yet vulnerable. There is a need to focus the public’s attention on the significance of the lakes for the region as a cohesive, binational whole. To address this need, build on existing water law, and engage the public, this Article provides a blueprint to establish a Great Lakes Trail on the shores of the Great Lakes. The Trail will link together 10,000 miles of coastline and provide the longest marked walking trail in the world. It will demarcate an already existing, yet largely unrecognized, public trust easement and engage the public with their common heritage in the lakeshore. The Great Lakes Trail is rooted in longstanding legal rights in the beach commons that have been forgotten and eroded over time. The Trail will provide a tangible way to restore the public’s coastal history and reinvigorate public trust rights. In the United States, when each of the Great Lakes states entered the Union, the federal government transferred to them the waters and lakebeds of the Great Lakes up to the ordinary high water mark on the beach. The states were to hold these lands and waters in trust for the public use and enjoyment. In 2005, the Michigan Supreme Court held in favor of the public’s right to access and walk along this beach. This is the only Great Lakes state court decision to directly address the public’s right to walk along the Great Lakes, and it provides an excellent contemporary model decision for the region. On the Canadian side of the Great Lakes, there is an existing movement to build a Waterfront Trail along all of the Great Lakes and St. Lawrence River, as well as legislative efforts to recognize a right of passage on foot along the Great Lakes shoreline. However, the states and provinces lack consistency in how they address public access to this coast, and have not identified it as a broad public asset like the Appalachian Trail. Establishing the Great Lakes Trail will be a monumental effort, requiring a multidisciplinary approach. It will require generating local, and especially lakeshore property owners’ support for the Trail; developing a system of local volunteers; working with artists and educators to design art installations and signs that reflect each community’s values and educate the public about Great Lakes ecological and legal issues; building local tourism economies with chambers of commerce to promote trail-oriented businesses; and partnering with GIS mappers and app developers to produce real time local business information and mapping. Ultimately, allowing people to utilize their public trust rights in walking the coasts of the Great Lakes actively engages them in seeing the importance of the Great Lakes as an ecological, political, economic, and cultural asset, which is a precursor to developing and implementing cooperative Great Lakes governance structures.
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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".