Through the teachings of the local marine life: A case study of students’, student-teachers’, teachers' and leaders’ perceptions of Ocean Wise selected programming
Bibliographic record
Abstract
Recently, the concept of ocean literacy (OL) has been described as a way forward to help communities and individuals develop a more holistic understanding of their influences on the ocean and the ocean's influences on their lives.Still, OL has not yet been fully enacted in the K-12 curricula in Canada and many environmental education programs are taking the lead to provide participants with this type of broader understanding.In this study, I provide a broad overview of OL initiatives as enacted by the Ocean Wise NGO (OW) and how these have influenced the diffusion of ocean literacy in British Columbia (BC).I selected a range of education programs for data collection including school visits to the Vancouver Aquarium, offsite mobile programming (with AquaVan), and teacher professional development programs, both onsite and with an online learning platform.Through an instrumental case study design, I combine qualitative approaches with observations, together with focus groups and interviews, and questionnaires to provide a broad view of activities from the perspective of program participants.In addition, I explore how the programs' approaches influence participants in becoming ocean literate.The results revealed that by providing locally referenced experiences with hands-on, the programs have positive impact in participants experiences and connection to the ocean.Although there are limitations in the delivery of ocean literacy, the selected OW programs play an important role on introducing key concepts of our relationship with the ocean and advancing ocean literacy in BC.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".