Bibliographic record
Abstract
Youth have the potential to play a key role in addressing the root causes of global climate change and in promoting a more sustainable local and global society. In this special issue, a group of scholars, representatives of community organizations, and young environmental leaders share what they have learned about engaging youth in six different countries in environmental action. The issue features Youth Leading Environmental Change (YLEC), a collaborative, evidence-based, multinational, youth-focused project and research study. The six participating countries include economically developing countries in the global South that face many impacts of climate change—Bangladesh, India, and Uganda—and economically “developed” countries in the global North that significantly contribute to climate change without facing comparable impacts—Canada, Germany, and the United States. Each country hosted one YLEC case study, which was anchored within a shared environmental justice framework, derived from the application of a common theory of engagement, and tailored to the local context. The YLEC workshop series used education to promote young people's engagement in environmental action that extends beyond their own lives to touch other people, communities, and systems. YLEC's use of multiple and varied components provided a comprehensive, holistic, critical, and action-oriented pedagogical approach, delivered in a format that prioritized community, mutual trust, participation, and peer-led learning. Across the contributions to this issue, readers will learn about the theory of engagement that informed the project, the results of a longitudinal mixed-method study assessing the main impacts on participants in all six countries, and a detailed analysis of how the program components were implemented and worked in creating changes in systems thinking among participants in three select countries. Key Words: Youth—Youth engagement—Environmental action—Environmental activism—Environmentalism—International—Environmental justice.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.203 | 0.115 |
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".