Student participation at the UNFCCC Convention of the Parties supports transformational learning and engagement on climate action
Bibliographic record
Abstract
Abstract When Swedish climate activist Greta Thunberg addressed world leaders at the United Nations Framework Convention on Climate Change (UNFCCC)’s 24th Conference of Parties (COP24), it was clear that young people are interested in and aware of their potential to influence international climate change negotiations. Young people also face barriers to effectively engaging in the COP processes with few opportunities to learn about the structure and practices for COP Observers. In this paper, we describe and evaluate a structured learning experience developed to support students conducting research related to climate change and their engagement with international climate negotiations. Before attending the COP24, students were given in-person and online training about the UNFCCC, its processes, and major issues under negotiation. They also developed and presented their work during a side event. Through pre- and post-surveys and in-depth interviews, we asked students about their expectations and degree of engagement and agency at the COP and more broadly on climate action. Students reported that the academic scaffolding before and during the COP provided them with tools for navigating the complexities of the COP. Despite the disengagement of some students, findings reveal that this learning experience supported self-efficacy and engagement in climate change action.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".