Rivers of the Anthropocene
Bibliographic record
Abstract
This exciting volume presents the work and research of the Rivers of the Anthropocene Network, an international collaborative group of scientists, social scientists, humanists, artists, policymakers, and community organizers working to produce innovative transdisciplinary research on global freshwater systems. In an attempt to bridge disciplinary divides, the essays in this volume address the challenge in studying the intersection of biophysical and human sociocultural systems in the age of the Anthropocene, a new geological epoch of humans’ own making. Featuring contributions from authors in a rich diversity of disciplines—from toxicology to archaeology to philosophy— this book is an excellent resource for students and scholars studying both freshwater systems and the Anthropocene. “Shows how human relationships with river systems changed along with transformations in society and culture. This book compels us to understand the historical perspectives on our relationship with nature that are so important in shaping our attitudes about both the environment and our own societies.” ANIK BHADURI, Executive Director of Future Earth’s Sustainable Water Future Programme and Associate Professor, Griffith University, Australia JASON M. KELLY is Director of the IUPUI Arts and Humanities Institute and Associate Professor of History at Indiana University–Purdue University Indianapolis. PHILIP SCARPINO is Director of the Public History Program and Professor of History at Indiana University–Purdue University Indianapolis. HELEN BERRY is Reader in British History and Dean of Postgraduate Studies at Newcastle University. JAMES SYVITSKI is Executive Director of the Community Surface Dynamics Modeling System and Professor of Geological Sciences at the University of Colorado Boulder. MICHEL MEYBECK is Emeritus Senior Scientist at the French National Center for Scientific Research and at the METIS laboratory at the University Pierre and Marie Curie (Paris 6).
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".