Community Knowledge and Concerns About Urban Soil Science, Practice, and Process: Perspectives From the Healthy Soils for Healthy Communities Initiative in Los Angeles, CA, United States
Bibliographic record
Abstract
Urban soil systems research has largely relied on the narrative that soils provide ecosystem services to human populations and should be studied and managed to maximize their potential value in regards to such services. However, soil scientists have not adequately engaged with diverse stakeholders to understand the needs, opportunities, and challenges related to urban soil systems. This disconnect has resulted in urban soil system research agendas that are potentially misaligned with the needs of the communities in which they are situated. Community engagement in the priorities-setting stage of research development can create research agendas that more closely align with community needs. Here we report on findings from the Healthy Soils for Healthy Communities Initiative in which community perceptions, needs, and concerns regarding soils in Los Angeles (LA) County, California, United States were measured through four county-wide online surveys with residents, educators, policy-makers, and professionals and a series of virtual focus groups with key community representatives. The online surveys revealed that the majority of LA County residents (76%) are very or extremely concerned about soil contaminants and pollution. Likewise, 70% of policy-makers and 77% of LA County professionals are highly concerned about soil contamination. In contrast, fewer LA County educators (48%) are concerned about soil contaminants and pollution. Even though 85% of LA County residents surveyed maintain some kind of green space, 70% self-report that their knowledge regarding factors impacting soil health is low. The focus groups revealed several themes present across stakeholder groups including a need for: (1) accessible and transparent soil data and testing; (2) effective community engagement and streamlined communication that centers underserved communities; and (3) building alliances among community, policy, businesses, and science professionals and leveraging connections among organizations, individuals, and agencies that are focused on soil. The findings from this study have informed the future direction of urban soil research and community science in the region. The process of engaging communities in defining research agendas can serve as a model for other cities providing an opportunity to not only improve the relevance and impact of urban soil research, but also improve the sustainability of urban soil systems.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".