Analyzing environmental communication and citizen science in the context of environmental monitoring and assessment for Agenda 2030 in rural settings of Chile and Sweden
Bibliographic record
Abstract
Introduction This article offers an analysis of environmental communication (EC) and citizen science (CS) in the context of Environmental Monitoring and Assessment (EMA) for the implementation of Sustainable Development Goal 15 (Life on Land) in Chile and Sweden. Methods The paper is based on fieldwork in two rural study areas of Chile and Sweden where we followed different CS initiatives in relation to EMA and Agenda 2030. We conducted interviews, analyzed documentation and conducted an SDG mapping workshop to understand the implementation of SDG 15 in these two rural forest settings. Results Our findings suggest that CS has potential as a democratic innovation for environmental governance in both countries. However, we also found important barriers to the legitimacy of CS as a feature of EMA and local environmental governance in both countries. The paper situates CS in the wider governance and environmental communication processes in regional politics surrounding implementation of national policies for the use of natural resources. Discussion The article offers new insights into the barriers and possibilities for public participation in environmental governance and policy at local levels, by addressing the interlinkages between environmental communication and citizen science in rural settings.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".