Urban Rivers: Remaking Rivers, Cities, and Space in Europe and North America
Bibliographic record
Abstract
Urban Rivers examines urban interventions on rivers through politics, economics, sanitation systems, technology, and societies; how rivers affected urbanization spatially, in infrastructure, territorial disputes, and in floodplains, and via their changing ecologies. Providing case studies from Vienna to Manitoba, the chapters assemble geographers and historians in a comparative survey of how cities and rivers interacted from the seventeenth century to the present.Rising cities and industries were great agents of social and ecological changes, particularly during the nineteenth century, when mass populations and their effluents were introduced to river environments. Accumulated pollution and disease mandated the transfer of wastes away from population centers. In many cases, potable water for cities now had to be drawn from distant sites. These developments required significant infrastructural improvements, creating social conflicts over land jurisdiction and affecting the lives and livelihood of nonurban populations. The effective reach of cities extended and urban space was remade. By the mid-twentieth century, new technologies and specialists emerged to combat the effects of industrialization. Gradually, the health of urban rivers improved.From protoindustrial fisheries, mills, and transportation networks, through industrial hydroelectric plants and sewage systems, to postindustrial reclamation and recreational use, Urban Rivers documents how Western societies dealt with the needs of mass populations while maintaining the viability of their natural resources. The lessons drawn from this study will be particularly relevant to today's emerging urban economies situated along rivers and waterways.
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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".