Global Environmental Change

Codes and data for "Democratization and Energies sources: are democracies more sustainable?"

Data represents content analysis of 169 articles published in U.S. mainstream newspapers covering ocean science reporting from 2001 through 2015. Articles were categorized according to dominant issue, basis of evidence provided, causal attribution, presence of solutions and uncertainty, and inclusion of doom and gloom as well as optimistic language.

R script developed for analysis.

Processed data accompanying article 'The role of global dietary transitions for safeguarding biodiversity.'

The file contains all 162 Intended Nationally Determined Contributions submitted to the UNFCCC, up to and including the 1st May 2016. These have been analysed and coded according to a range of 'concepts' identified by the coders.

This Excel file contains three pages of data: 1. Data for all documents reviewed. 2. Data for documents that were explicitly framed as mountain and adaptation focused. 3. Summary statistics for both sets of documents. For pages 1 and 2, columns represent questions asked about each document. See the Questionnaire and Codebook in the article’s Supplementary Materials for details about questions as well as descriptions for possible response options. For pages 1 and 2, values in Column A “PR” and “GL” stand for per-reviewed and grey literature, respectively. For pages 1 and 2, each row represents a ‘discrete adaptation initiative’. Discrete adaptation initiatives are defined as actions that are distinct in their timing, form, intent, or scope. One document may report several discrete adaptation initiatives. For pages 1 and 2, raw data is disaggregated in columns AO - GF to facilitate analysis.

Data and replication files (STATA 13 format) for the paper: Climate Change and Migration: Is Agriculture the Main Channel? (Chiara Falco, Marzio Galeotti and Alessandro Olper)

Data and codes attached to the paper "Fire risk explains persistent poverty and fire use in the Brazilian Amazon"

cls_protection_publication: for each coastline-segment used in the study and each scenario combination used the protection decision (binary: 0/1) country_output_publication: time-resolved country level data on protected coast, seaflood cost and protection cost for each scenario combination global_output_publication: : time-resolved global data on protected coast, seaflood cost and protection cost for each scenario combination

We provide data for Experiments 1 and 2 of the manuscript "What makes for compelling science? Evidential diversity in the evaluation of scientific arguments". We also provide robustness checks for the cauchy prior widths of our Bayesian null hypothesis tests as mentioned in footnote 4 of the manuscript.