Overlooked No More: Empowering Youth Voices in Global Climate-Change Negotiations
Bibliographic record
Abstract
Youth participation in climate change negotiations has increased over the last decade; however, youth voices are still underrepresented. The diversity of youth activists in the Americas and the sheer number of youth-led organizations belies any stereotypes about disinterested youth. Youth care about both the present and the future of our planet; are organizing; and have many voices. Yet, there are currently weak institutional mechanisms to integrate these voices into climate negotiations beyond showcasing experiences. Youth must be included in collaborative and transdisciplinary ways. We recommend opportunities that have had success in Latin America and the Caribbean (LAC), which help youth to engage in discussions with policymakers to inform climate negotiations. These recommendations include the following: 1) institutionalizing formal national and regional youth councils and committees to strengthen collaboration between young people and decision-makers; 2) creating and expanding training programs for youth on climate negotiations; 3) using science diplomacy as a key tool to enhance science-based, relevant, and collaborative efforts for youth engagement; and 4) developing strategies to navigate the diversity of expertise, scientific knowledge, and inclusion of youth to address equitable climate solutions.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".