Challenges For Managing The North American Coastal Zone
Bibliographic record
Abstract
Canada, the United States and Mexico are adjacent coastal nations where the impact of significantly increased human activity in the coastal zone by the year 2050 will be potentially catastrophic. Integrated Coastal Management (ICM) may well have a role to play within and between all three countries to help ameliorate this situation. This paper looks at the challenges facing sub-continental ICM, from institutional foundations to large-scale environmental management practices that cross political and cultural boundaries. To assist in this discussion, we have analyzed the overlapping sets of political-administrative units within terrestrial ecosystems, especially those with complex landscape attributes, to arrive at a series of issues that help identify areas of convergence and joint action as well as barriers to action. Finally, we look at landscape attributes on a regional scale to show that joint institutional initiatives that recognize existing ecological, socio-economic, and political-administrative differences between Canada, the United States and Mexico need to be built.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".