Indigenous resurgence in the Blue Economy: Relational values to guide kelp mariculture
Bibliographic record
Abstract
Abstract Decisions about how to use ocean spaces are increasingly attuned to issues of social equity, environmental sustainability and climate resilience, yet often bypass local governance, knowledge, values and thus objectives. To inform future decisions about kelp harvest and mariculture activities on the west coast of Canada, we co‐designed research questions and methods with the Kwakiutl Nation to co‐produce a social‐ecological decision space. Specifically, we documented ancestral Kwakiutl governance principles that guide human–kelp relationships, quantified contemporary community values of kelp and envisioned future kelp management actions that would support social‐ecological system resilience. We found that Kwakiutl governance principles of respect, reciprocity, ‘we are all one’ and responsibility are foundational to human–kelp relationships. Moreover, the Kwakiutl valued kelp for its relational and indirect uses, such as it being present for future generations and part of a healthy ocean, more than the direct use of kelp as income. Strategic management actions, including the resurgence of Kwakiutl harvest practices and knowledge, were identified as ways to support future climate resilient kelp harvest and mariculture. While there is interest in developing nation‐owned kelp mariculture operations to participate in the burgeoning ‘Blue Economy’, financial gain is less important than sustaining wild kelp forests and re‐establishing human–kelp relationships within the Kwakiutl community. These results emphasize that, within the Kwakiutl Nation, non‐economic values guide the decision‐making space surrounding emerging kelp industries. As countries worldwide develop Blue Economy policies, they can prioritize equitable governance and social‐ecological sustainability by guiding place‐based management with local values, knowledge and governance principles Read the free Plain Language Summary for this article on the Journal blog.
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.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".