Capacity building in stakeholders around Detroit River fish consumption advisory issues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Detroit River is an international water body that has several fish consumption advisories for contaminants that affect human health and economic revenue for the USA and Canada. Despite the importance of these advisories, little progress has been made in developing effective management strategies or coordinating monitoring, research, and policy efforts between the 2 nations. We engaged 44 stakeholder organizations to increase community capacity on these issues for the Detroit River. We assessed capacity with key informant interviews and a network survey. Our analysis identified weak ties in information sharing and collaboration between countries. We used this information to improve stakeholder capacity, which included forming working groups that focused on system analysis, identification of priority issues, and definitions of organizational roles. Outcomes included outreach materials addressing environmental-justice issues and risk-analysis models of polychlorinated biphenyl (PCB) body burdens in fish. Our assessment of workshop participants with a longitudinal survey indicated that we increased network capacity and issue awareness in our stakeholders by providing new ways for them to work together. The engagement of stakeholders also improved research outcomes. By identifying stakeholder concerns related to scientific questions about consumption advisories early in the process, researchers were able to direct their efforts to generating translational research that better addressed stakeholder needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it