From Yellowstone to Australia and New Zealand: National Parks 2.0
Bibliographic record
Abstract
Abstract Following the establishment of the world's first national park at Yellowstone (USA) in 1872, the concept was rapidly transferred to Australia, New Zealand and Canada. This article examines this second wave of adoption – and adaption – focussing on five case studies from Australia and New Zealand. While Yellowstone provided the inspiration for further national parks and protected areas, what was developed was often very different from the American template. Some of these national parks were quite small and some primarily orientated towards recreation. The New Zealand examples were profoundly shaped by interactions with the indigenous peoples, whereas the Australian ones were not. By early in the twentieth century, this second wave was beginning to focus on protecting specific ecosystems and wildlife, developments well in advance of the USA at that time. In taking the Yellowstone model and greatly adapting it for a variety of different social, political and physical environments, this second wave laid the foundations for the internationalisation of the national parks concept.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.021 |
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; both teacher heads agree on what is shown here.
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".