Recovery or continued resuscitation? A clinical diagnosis of Colorado River sub-basin recovery programs
Bibliographic record
Abstract
With a particular emphasis on the Upper Colorado River Endangered Fish Recovery Program (UCR-EFRP) and Lower Colorado River Multi-Species Conservation Program (LCR-MSCP), we analyze, for each program, four system properties that contribute to resilience: system architecture, which includes (1) connectivity and distribution and (2) assemblage of system elements; and system dynamics, which includes (3) social and natural capital flows and (4) system renewal and continuation. Each of these system properties is analyzed based on specific social and corresponding biophysical indicators. The system properties were ranked on a carefully constructed scale based on gradations of each system property (derived from the literature) on both social and biophysical indicator standing. Our results indicate that the UCR-EFRP has relatively better social architecture and dynamics with relatively less impact on the ecological architecture and dynamics compared to the LCR-MSCP, though this result may be a function of the greater amount of infrastructural constriction and path dependence in the lower basin compared to the upper basin. We conclude by suggesting that a transformative pathway forward needs greater adaptability and flexibility incorporated into the social architecture and dynamics to move toward better ecological health of the river.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".