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ispartof: CAMPBELL SYSTEMATIC REVIEWS vol:16 issue:4 status: published

The volume of published academic research is growing rapidly and this new era of “big literature” poses new challenges to evidence synthesis, pushing traditional, manual methods of evidence synthesis to their limits. New technology developments, including machine learning, are likely to provide solutions to the problem of information overload and allow scaling of systematic maps to large and even vast literatures. In this paper, we outline how systematic maps lend themselves well to automation and computer‐assistance. We believe that it is a major priority to consolidate efforts to develop and validate efficient, rigorous and robust applications of these novel technologies, ensuring the challenges of big literature do not prevent the future production of systematic maps.

Should economic growth continue in a world threatened by the prospect of catastrophic climate change? The scientific and public debate has brought forth a broad spectrum of views and narratives on this question, ranging from neoclassical economics to degrowth. We argue that different positions can be attributed to underlying differences in views on (a) factors that determine human well‐being, (b) the feasibility and desirability of economic growth, (c) appropriate intervention points, and (d) preferences about governance and policy options. For each of these dimensions, we propose points of agreement on which a consensus between conflicting positions might be achieved. From this basis, we distill a sustainability transition perspective that could act as a basis for a renewed debate on how to align human well‐being with environmental sustainability. This article is categorized under: Climate Economics>Economics and Climate Change