Contributions, missed opportunities, and future directions: A critical reflection on global climate change and environmental sustainability in <i>AJCP</i> over five decades
Bibliographic record
Abstract
In this contribution to the 50th Anniversary Special Issue, the authors consider how global climate change and environmental sustainability have been addressed in the American Journal of Community Psychology (AJCP) over the last five decades. As we are increasingly exceeding critical planetary boundaries (global climate change, biodiversity loss, land degradation, etc.) with disastrous impacts on human well-being-especially for peoples already marginalized-it is timely to consider the treatment of environmental issues in the history of the AJCP and in community psychology more broadly. This review of relevant articles is clustered into three topics derived from our critical understanding of the articles themselves: (a) public participation and power; (b) community-level responses to environmental change, including its disproportionate impacts on marginalized groups; and (c) frameworks and worldviews that integrate the natural world as necessary context for research and action. The commentary on the featured articles is framed in terms of their key contributions, missed opportunities up to this point, and future directions for the field. While looking back at the past 50 years, the authors also have an eye to the years ahead and what work can be done to mitigate the harms of climate change, adapt to the emerging new environmental reality, and promote just and inclusive sustainabilities worldwide.
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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 | 0.043 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.030 | 0.057 |
| Insufficient payload (model declined to judge) | 0.004 | 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".