Bibliographic record
Abstract
This chapter outlines the ways in which fresh water is crucial to all of us in myriad ways, and the challenges we face when disrupting natural hydrodynamic systems. Since improvements made in sanitation in the nineteenth century, wealthy countries have largely alleviated the effects of water-borne disease and lack of safe drinking water. However, it is precisely modern, urbanized society that has caused the most damage to marine systems, through pollution, eutrophication (introduction of nutrients) and hydro-electric dams, in service of its industrial development. For developing countries, the UN’s Sustainable Development Goals (SDGs) recognized, in 2015, the increasing need for access to safe drinking water. The chapter emphasizes that the past models of water management in industrialized nations, which have come at huge ecological and social costs, should be regarded critically by developing regions, desperate to utilize water systems for growing urban populations. Hering advocates learning from the successes and failures of wealthy countries; developing sustainable, balanced approaches to agriculture (particularly the use of fertilizer) and waste management; and implementing decentralized, locally-appropriate methods of water-management.
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.
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 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.171 | 0.029 |
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; both teacher heads agree on what is shown here.
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".