Perpetual planning: Expertise, uncertainty, and the politics of delay in Colombia's Guayuriba river-basin
Bibliographic record
Abstract
Perpetually planning the Guayuriba River basin for nearly two decades has allowed mining companies to continue extracting gravel, amidst uncertain flooding dynamics; oil companies to continue discharging production waters, despite uncertain water quality; and palm oil plantations to continue large-scale irrigation, notwithstanding uncertainties in water use and availability. Drawing on ethnographic fieldwork and semi-structured interviews in the Guayuriba River basin of the Eastern Foothills of Colombia, we discuss the temporality of planning, the rituals of expertise and public participation, and the accrual of uncertainties related to flooding, water quality, and water use and availability. Uncertainties have been perpetuated, accumulated, obscured, and met with a lack of will throughout the continual revision and adjustment of the river-basin planning document. While peoples and natures are made to wait, perpetual planning has in fact led to a tacit authorization of increased resource extraction despite concerns of environmental degradation. By embracing uncertainty as an inherent aspect of the system, we can envision a planning process that would prioritize local knowledge and experiential insights over detached expertise, reshaping the dynamics of knowledge dissemination in the region and mitigating the potential for corrupt practices, allowing our engagement with uncertainty to evolve as we interact with the world.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".