Bibliographic record
Abstract
Citation (2015), "List of Contributors", Climate Change, Culture, and Economics: Anthropological Investigations (Research in Economic Anthropology, Vol. 35), Emerald Group Publishing Limited, Bingley, pp. ix-x. https://doi.org/10.1108/S0190-128120150000035018 Publisher: Emerald Group Publishing Limited Copyright © 2015 Emerald Group Publishing Limited Olivia Barnett-Naghshineh Anthropology, School of Social Sciences, University of Auckland, New Zealand Ana Maria de Souza Mello Bicalho Departamento de Geografia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil Sophie Bouly de Lesdain EDF Research & Development, Associate IIAC LAU Lab (CNRS-EHESS), Clamart, France Jane I. Guyer Department of Anthropology, Johns Hopkins University, Baltimore, MD, USA Scott William Hoefle Departamento de Geografia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil Hao Li Changjiang River Scientific Research Institute, Changjiang River Water Commission, Wuhan, China Ty Matejowsky Department of Anthropology, University of Central Florida, Orlando, FL, USA Patrick B. Patterson Population Health and Inequities Research Centre, O’Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada Victoria C. Ramenzoni Social Science Team, Office of Program Planning and Integration, National Oceanic and Atmospheric Administration, Department of Commerce, Silver Spring, Maryland, USA Richard K. Reed Department of Sociology and Anthropology, Trinity University, San Antonio, TX, USA Pasang Yangjee Sherpa Department of Anthropology, Pennsylvania State University, University Park, PA, USA Monica L. Smith Department of Anthropology, University of California at Los Angeles, CA, USA Meine Pieter van Dijk UNESCO-IHE Institute for Water Education, Delft, and Maastricht School of Management, Maastricht, Netherlands Donald C. Wood Department of Medical Education, Akita University Graduate School of Medicine, Akita, Japan Book Chapters Climate Change, Culture, and Economics: Anthropological Investigations Research in Economic Anthropology Climate Change, Culture, and Economics: Anthropological Investigations Copyright Page List of Contributors Editorial Advisory Board Introduction Part I: Local Cultural Adaptations/Adjustments Institutional Climate Change Adaptation Efforts among the Sherpas of the Mount Everest Region, Nepal Installing Rooftop Solar Panels in Private Homes: The Case of Small Electricity Producers on Reunion Island (Indian Ocean) “Bug Wood”: Climate Change, Mountain Pine Beetles and Risk in the Southeastern BRITISH COLUMBIA Logging Industry Part II: Food Production/Procurement Conservation Units, Environmental Services and Frontier Peasants in the Central Amazon: Multi-Functionality, Juxtaposition or Conflict? Global Warming or Cash Economy? Discourses of Climate Change and Food in Eastern Highlands Province, Papua New Guinea Farmers’ Rainfall Anticipation: Incidence and Patterns in Western Nigeria. Advantages of Focus and Problems of Extrapolation in Case Studies Climate Change Policies and Adaptive Behavior of Farmers in Southern China Is Environmental Uncertainty Redefining Fishing Strategies? The Use of the Traditional Lunar Calendar to Allocate Fishing Effort in Ende, Eastern Indonesia Part III: Urban Situations The Origins of the Sustainability Concept: Risk Perception and Resource Management in Early Urban Centers Merchant Resiliency and Climate Hazard Vulnerability in the Urban Philippines: Anthropological Perspectives on 2011 Typhoons Nesat and Nalgae Environmental Destruction, Guaraní Refugees, and Indigenous Identity in Urban Paraguay About the Authors
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.749 | 0.737 |
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; the direct Gemma label and the distilled Codex classifier 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".