Encouraging youth engagement in marine protected areas: A survey of best practices in Canada
Bibliographic record
Abstract
Abstract A holistic approach to stakeholder participation is emerging where youth are increasingly being recognized as core stakeholders in community‐based conservation efforts. A growing number of youth‐focused marine conservation initiatives and representation at international marine conservation conventions demonstrate that youth are taking an active role in marine conservation worldwide. This paper surveys current best practices in youth engagement in marine protected areas (MPAs) in Canada, across 10 different engagement strategies. These are: facilitate learning through experiential education; include studies of MPAs in academic and community programmes; utilize multimedia opportunities, including social media, film, website, and apps; provide meaningful volunteer opportunities; deliver professional development sessions for youth initiative building; create youth councils to assist organizations in an advisory role; hire youth for employment in internships, co‐ops and junior positions within organizations; showcase young people as Youth Ambassadors of MPAs; share opportunities through effective outreach and promotion; and, integrate under‐represented perspectives in MPAs. Recommendations are drawn from the case studies within each engagement strategy. Collectively, they offer insight into the variety of ways the international community can support, highlight and advance youth participation in MPAs.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".