Empowering her guardians to nurture our oceans future
Bibliographic record
Abstract
Coastal Indigenous and Traditional Peoples communities are starting to see changes to their lives from climate change, whether this is from species range change or displacement from land changes. For many of these communities the ability to adequately adapt to these changes is limited by the governance structures they are required to live within, which differ from their customary practices and culture. A group of Indigenous and Traditional Peoples attended the Future Seas 2030 workshop in November 2019 and discussed the consequences of climate change along with the biggest barriers for their communities to contribute towards more sustainable future using traditional knowledge that will benefit all of earth's people. The aim of this was to highlight and give voice to the various backgrounds and real-life situations impacting on some of the world's Indigenous and Traditional Peoples whose connection with the oceans and coasts have been disrupted. The paper raises issues of oppression, colonisation, language and agency on why it has been difficult for these groups to contribute to the current management of oceans and coasts, and asks scientists and practitioners in this space to become allies to enable the needed shift for earth's guardians to take a leading role in nurturing her for our future.
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 | 0.000 | 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 | 0.020 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".