Holomua Marine Initiative: community-generated socio-cultural principles and indicators for marine conservation and management in Hawaiʻi
Bibliographic record
Abstract
Marine managers commonly use ecological indicators in planning and evaluations; however, few programs monitor social and cultural impacts of management. Practical approaches to identifying and monitoring social and cultural aspects of communities’ relationships with their environment could assist many agencies in understanding the impacts of their efforts to achieve conservation goals. The Hawaiʻi Department of Land and Natural Resources, Division of Aquatic Resources (DAR) launched the Holomua Marine Initiative to collaborate and engage with communities to strengthen co-management efforts, which included integrating socio-cultural aspects into the planning and assessment of marine management. Our team, which included resource managers, Western and indigenous scientists, community leaders, students, agency, and university staff engaged in collaborative management efforts in Hawaiʻi, developed an approach to monitor the social and cultural impacts of DAR’s management actions. Through online collaborative workshops with community members and non-profit leaders engaged in marine conservation in Hawaiʻi, we co-developed socio-cultural principles and indicators based on their reciprocal relationships with the nearshore environment. During the workshops, we used small group activities, snow cards, sorting, and categorization to generate nine fundamental principles, with associated indicators, to guide marine management in Hawaiʻi. Many of the principles and indicators are comparable to those developed in other parts of the Pacific, revolving around themes including the perpetuation of local and indigenous knowledge across generations, and access to land and natural resources. Participants also suggested themes less prevalent in other research, such as the need to evaluate impacts of tourism on community relationships with coastal areas. We offer recommendations for the development of socio-cultural principles and indicators in other place-based contexts, and emphasize the importance of on-going community collaboration. Developing a socio-cultural monitoring framework with community members impacted by marine management decisions could enable others engaged in collaborative efforts, including government agencies, to holistically understand and address impacts of their policies and actions. Monitoring layered socio-cultural impacts of marine management on local and indigenous communities has the potential to shift management goals, and enhance long-term effectiveness and support for initiatives to protect coastal resources worldwide.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".