Ocean Economy Valuation Studies in the Asia-Pacific Region: Lessons for the Future International Use of National Accounts in the Blue Economy
Bibliographic record
Abstract
There have been several projects that have addressed the challenges of measuring the ocean economy in the Asia-Pacific region. The paper examines some lessons from these projects and the implications for the future use of national accounts. Following the Asia Pacific Economic Cooperation (APEC) Bali declaration, the APEC Marine Resource Conservation Working group’s “Measuring the Marine economy” project promoted consistent measurement of the marine economy across the 21 APEC economies against a list of agreed marine industry categories which was developed by an APEC workshop on Easter Island in 2004. In 2008-09 a Partnership for the Environmental Management of the Seas of the East Asia (PEMSEA) worked with national marine economists in eight countries and revealed that some East Asian ocean economies had substantially higher marine economy as proportion of GDP than in more developed economies. In the past five years China has progressed several Blue economy forums. There have been several South East Asian Seas initiatives, such as the Changwon declaration, leading to a new PEMSEA project to measure the Blue economy for East Asian economies in 2015-2018. The drivers to measure the Ocean economy are an outcome of regional initiatives and Ministerial declarations. Few government national account agencies see a need to supply ocean economy data and studies have been undertaken by academics and consultants with access to national account information. Ocean policy development in Australia, Canada and the US has produced some studies. Marine industries are highly regulated and the government vision for oceans lies across many different agencies. In the Asia Pacific use of national accounts to provide industry estimates acknowledge the three pillars of sustainability, with social and environmental impact being important in these developing countries. There are different perspectives on the relevance of national accounts to green, blue economy valuation seeming to be less valued than less tangible environmental valuation approaches. The paper concludes that National accounts are necessary to blue economy evaluation, if not sufficient in all aspects and provide a solid basis for improvements in measurement of the Blue economy.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".