Coming to Terms with Ocean Literacy
Bibliographic record
Abstract
The term “ocean literacy” originated in the early 2000s from American ocean science researchers and educators to strengthen ocean science education in the national curriculum. Worldwide, it has been adapted to reflect a more multidisciplinary approach to understanding humans’ relationships with the ocean. Research from the Understanding Ocean Literacy in Canada national study (2019-2020) (Ammendolia et al., 2020; Glithero, 2020; Hoover, 2020; MacNeil, 2020; Ostertag & Ammendolia, 2020; Yumagulova, 2020) identified ocean literacy as a limiting term, unable to capture the scope of Canadian experiences with the ocean continuum (land, freshwater, coastal areas, sea ice, open ocean), and inadequate in encapsulating different worldviews and across different linguistic communities. We discuss the challenges of contextualizing an international term within Canada and present ideas to move toward more inclusive terminology, examining the challenges still ahead in developing relevant terminology and bridging with international initiatives.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.017 | 0.041 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".