Finding the “Just Right” Tools for Environmental Geochemistry Research at the Tar Creek Superfund Site Ottawa County, OK
Bibliographic record
Abstract
How do formal and informal land use changes have the potential to create unique, and potentially synergistic, risks to communities? Traditionally environmental geochemists privilege certain analytical approaches to evaluate the risk in a system, but when using a participatory approach, the emphasis is instead placed on using the “just right” tools co-discovered with members of the community. In this study we partnered with the LEAD Agency, an environmental advocacy group with a long history of co-designing research agendas to address community concerns to study trace legacy metals in floodplain soils at the Tar Creek Superfund Site in Ottawa County, Oklahoma. At Tar Creek, large mine waste (chat) piles and acid mine seepage have contaminated surrounding communities with zinc, lead, and cadmium. Heavy metal contamination of floodplains at mining sites like Tar Creek involve a complex set of biogeochemical interactions that are controlled by land use patterns (e.g. reworking chat piles and downstream dams), transport pathways, and changing climate making it difficult to prioritize interventions aimed at reducing exposure. Using a participatory research approach, this study integrates (1) community initiated geochemical investigation of wind transportable Pb, (2) monitoring of nutrient loading to assess potential for eutrophication, which would increase metal transport and mobility in Tar Creek, and (3) examines the connections between social and political issues at Tar Creek and how these affect both scientific research and what remediation strategies are tenable. Our action based research aims to support our community partners in their goals:(1) to establish the Rights of Tar Creek through LEAD’s Clean Water Protection Ordinance, which would establish the right to clean water and legally recognize the rights of Tar Creek to exist, regenerate, and flourish, and (2) to expand the EPA’s definition of OU5, which would increase funding for remediation in Ottawa County.
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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 | 0.005 | 0.006 |
| 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 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".