Protecting Blue Horizons – A role play to make an MPA work
Bibliographic record
Abstract
Human activities are the major cause for what has been recognized as the 6th Mass Species Extinction. It is thus important to spread knowledge and raise awareness about the issues because we depend on biodiversity in ways that are not always apparent or appreciated. In December 2022, delegates from 196 governments adopted the Kunming-Montreal Global Biodiversity Framework (GBF) under the UN Convention on Biological Diversity (CBD). The GBF supports the achievement of the Sustainable Development Goals and sets out an ambitious pathway towards living in harmony with nature by 2050. Meanwhile, the lengthy ratification process is no guarantee of full enforcement after entry into force. Typically, different interest groups may resist top-down measures affecting them. This is known as the implementation gap of international treaties and agreements. Here we describe a role play intent on matching a key element of the top-down GBF, namely the establishment of interconnected marine protected areas (MPAs), with bottom-up awareness raising and deliberation among diverse stakeholders. Eleven characters of stakeholders have been developed through wide-ranging interviews and literature research. For each stakeholder an information sheet explains the context and his or her role. Based on the interviews, a general introduction and guidance for a moderator is provided together with a tentative schedule. Emphasis is placed on allocating sufficient time for the debriefing after a round of deliberations aiming at consensus towards establishing an effective MPA. The assumption is that the debriefing produces most learning about why biodiversity protection is essential and how to sustain a respectful dialogue process with persons holding different positions from one’s own. A first round of tests with young adults has already generated useful feedback allowing some improvements of the initial set. We propose the role play for wider use as a low-entry support for bottom-up participation in GBF implementation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".