Fostering Critical Thinking about Climate Change: Applying Community Psychology to an Environmental Education Project with Youth
Bibliographic record
Abstract
This article argues for the participation of community psychology in issues of global climate change. The knowledge accumulated and experience gained in the discipline of community psychology have great relevance to many topics related to the environment. Practitioners of community psychology could therefore make significant contributions to climate change mitigation. To illustrate this assertion, we describe an education project conducted with youth engaged in a community-based environmental organization. This initiative was motivated by the idea that engaged and critically aware youth often become change agents for social movements. Towards this purpose, rather than using mass marketing strategies to motivate small behavior changes, this project focused intensively on a few youth with the vision that these youth would also influence those around them to rethink their environmental habits. This project was influenced by five community psychology concepts: stakeholder participation, ecological and systems thinking, social justice, praxis, and empirical grounding. In this article we discuss the influence of these concepts on the project’s outcomes, as measured through an evaluative study conducted to assess the impacts of the project on the participating youth in terms of their thinking and action. The contributions of community psychology were found to have greatly impacted the quality of the project and the outcomes experienced by the youth.
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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 | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".