Mislabeling marine protected areas and why it matters—a case study of Australia
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 As part of international obligations and national policies, most nations are working toward establishing comprehensive, adequate, and representative systems of terrestrial and marine protected areas (MPAs). Assigning internationally recognized International Union for Conservation of Nature (IUCN) protected area categories to these MPAs is an important part of this process. The most recent guidance from the IUCN clearly states that commercial or recreational fishing is inappropriate in MPAs designated as category II (National Park). However, in at least two developed countries with long histories of protected area development (e.g., Canada and Australia), category II is being assigned to a number of MPAs that allow some form of commercial or recreational fishing. Using Australia as a case study, this article explores the legal and policy implications of applying protected area categories to MPAs and the consequences for misapplying them. As the Australian Government is about to embark on potentially one of the largest expansions of MPA networks in the world, ensuring the application of IUCN categories is both transparent and consistent with international practice will be important, both for the sake of international conventions and to accurately track conservation progress.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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