Water challenges at the U.S.-Mexico border: learning from community and expert voices
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
We discuss the results of a multi-dimensional learning process (expert surveys, community workshops) addressing water challenges at the U.S.-Mexico border. The grand institutional and political framework of the international border, and the tensions and gaps in it, dominates the water literature and expert concerns. However, social inequality and spatial and temporal diversity on both sides of the border emerge as important considerations from community input. Our goal is to make planning for regional water sustainability more comprehensive, both spatially and temporally, and more community responsive in a context of important divisions and inequalities. This is because the “sustainability” frame, as operationalized in resource bureaucracies and academic research, focuses on long-term ecosystem dynamics and supplies of fundamental resources. In this region, however, a supply emphasis on transboundary water quantity hides urgent matters of well-being and justice. For instance, community consultation emphasized two more immediate water issues: water quality, especially microbial issues, and localized catastrophic flooding amid general water scarcity. Understanding how adaptation to environmental change can be pursued efficiently and equitably will require convergent sustainability knowledge and action that addresses multiple sources of risk and potential resilience/adaptation. Framing these within an analysis of social vulnerability can help us to better understand patterns of risk produced by changes in earth systems and act effectively and efficiently to address them in equitable ways. Such a frame is particularly relevant to the U.S.-Mexico border region because of the large vulnerable populations on both sides and comparatively low capacity for collective and household-community resilience on the Mexican side of the border.
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 | 0.000 | 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 | 0.001 | 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) | 0.003 | 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 it