An Evaluation of the Marine Zoning and Aquaculture Plans in theGreat Sandy Region, Australia: Indicators for Successful IntegratedCoastal Zone Management
Bibliographic record
Abstract
The Great Sandy Region is a pristine sandy area off the eastern coast of Queensland, Australia. Due to the unique make-up of the region, integrated coastal zone management (ICZM) is evident: there are many management plans in place to ensure the longevity of the region’s natural resources. Inthis paper, qualitative environmental indicators were used to evaluate the strengths, weaknesses, and gaps in the Great Sandy Marine Park Zoning Plan (GSMPZP) and the Great Sandy Regional Marine Aquaculture Plan (GSRMAP). The GSMPZP is extremely comprehensive in nature, yet fails to define its overarching goal, and failed to involve the public during the planning process. Conversely, the GSRMAP demonstrated public participation and transparency throughout its planning process, yet fails to define maximum culture density of the aquaculture sites: this has serious implications for the health of the surrounding environment. It is recommended that, in the future, the GSMPZP adopt an adaptive management practice and involve the public in the planning process. Additionally, it is recommended that the GSRMAP explicitly defines maximum allowable culture density, and monitors the region closely after aquaculture begins to avoid regional environmental degradation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".