Doubling Down on Wicked Problems: Ocean ArtScience Collaborations for a Sustainable Future
Bibliographic record
Abstract
The UN Decade of Ocean Science for Sustainable Development recognizes the current ocean sustainability crisis and calls for a transformation of ocean science. Many of the key challenges recognized by the UN Decade are examples of wicked problems: intractable and messy situations with high stakeholder divergence. Addressing wicked ocean sustainability problems requires adaptable, iterative, and participatory approaches that can embrace multiple ways of knowing. It also requires a re-imagining of our relationship with the Ocean from extraction and resulting environmental degradation, towards the building of a sense of connection and stewardship. We propose ArtScience as a means to this end by highlighting how transdisciplinary collaborations can help create sustainable ocean futures. We reflect on a recent ArtScience event emerging from Ocean Networks Canada’s Artist-in-Residence programme. By situating ArtScience in a broader context of inter- and transdisciplinary collaborations, we demonstrate how ArtScience collaborations can help transform ocean science by envisioning previously unimagined possibilities, and establishing and strengthening relationships with diverse stakeholders through long-term mission-driven or place-based inquiry. We conclude with a call to action to acknowledge the potential these collaborations hold for addressing the challenges of the UN Ocean Decade.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.009 |
| 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".