Getting Off the Boat: Re‐Considering Research Responsibility and Knowledge Dynamics in Ocean Literacy
Bibliographic record
Abstract
In light of the UN Ocean Decade’s calls for increased ocean literacy, what can critical perspectives on inter‐epistemic exchanges contribute to the practice of researchers themselves? Herein, we aim to expand on scholarship analyzing the relationship between researchers and local/Indigenous knowledge holders beyond notions of knowledge commensurability, towards interpersonal practices. A framework of relationship‐building allows local perspectives and knowledge to be included both actively and passively in research. However, this requires marine scientists to spend time disembarked from sampling vessels in local communities. This adaptation in research methodology involves the scientist becoming a person first, and a researcher second. A paradigm shift occurs where the researcher’s function is that of a guest, whose primary exercise is to actively listen. This repositions ocean literacy as a reciprocal process, whereby the scientist learns from diverse perspectives to inform and enrich mutual understandings of the ocean. We build here on research experiences to show how interpersonal relationships, rather than systemic ones, can help build richer collaboration. This dynamic is illustrated through the case of a marine habitat mapping study in the Canadian Arctic. Community engagement was prioritized by the researcher as a first step, allowing for exposure to local understandings of the ocean to orient research questions. Outcomes included locally relevant marine maps and research findings, culturally responsive outreach materials, a recovered airplane, short‐term local employment, and long‐term relationships which continue to the present day. This case demonstrates how the intentional development of interpersonal relationships can leverage research activities towards building ocean literacy which respects and recognises diverse knowledge systems.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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".