An ever-growing body of evidence suggests that climate change is already impacting human and natural systems around the world. Global environmental assessments assessing this evidence, for example by the Intergovernmental Panel on Climate Change (IPCC) 1 , face increasing challenges to appraise an exponentially growing literature 2 and diverse approaches to climate change attribution. Here we use the language representation model BERT to identify and classify studies on observed climate impacts, producing a machine-learning-assisted evidence map which provides the most comprehensive picture of the literature to date. We identify 100,724 (62,950 − 162,838) publications covering a broad range of impacts in human and natural systems across all continents. By combining our spatially resolved database with human-attributable changes in temperature and precipitation on the grid cell level, we infer that attributable climate change impacts may be occurring in regions encompassing 85% (80%) of the world's population (land area). Our results also reveal a substantial 'attribution gap' as robust evidence for attributable impacts is twice as prevalent in high income compared to low income countries. While substantial gaps remain on con dently establishing attributable climate impacts at the regional and sectoral level, our unique database illustrates the broad extent to which anthropogenic climate change may already be impacting natural systems and societies across the globe. MainThere is overwhelming evidence that the impacts of climate change are already being observed in human and natural systems 3 . These effects are emerging in a range of different systems and at different scales, covering a broad range of research elds from glaciology to agricultural science, and marine biology to migration and con ict research 1 . The evidence base for observed climate impacts is expanding 4 , and the wider climate literature is growing exponentially 5,6 . Systematic reviews and systematic maps offer structured ways to collectively identify and describe this evidence while maintaining transparency, attempting to ensure comprehensiveness and reduce bias 7 . However, their scope is often con ned to very speci c questions covering no more than dozens to hundreds of studies.In the climate science community, evidence-based assessments of observed climate change impacts are performed by the Intergovernmental Panel on Climate Change (IPCC) 1 . Since the rst Assessment Report (AR) of the IPCC in 1990, we estimate that the number of studies relevant to observed climate impacts published per year has increased by more than two orders of magnitude (Fig. 1a). Since the third AR, published in 2001, the number has increased ten-fold. This exponential growth in peer-reviewed scienti c publications on climate change 5,6 is already pushing manual expert assessments to their limits. To address this issue, recent work has investigated ways to handle big literature in sustainability science by scaling systematic review and map methods to large bodies ...

When matched groups are examined and dialect-strategic scoring is used, sentence recall yields moderate-to-high levels of diagnostic accuracy to identify SLI within speakers of nonmainstream dialects of English.

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This paper will examine the role of various factors in affecting the salience, and hence the accessibility to pronominal reference, of entities introduced into a discourse by a full clause. We begin with the premise that the possibility of pronominal reference with it versus that depends on the cognitive status of the referent, in the sense of Gundel, Hedberg and Zacharski (1993). This formulation of the problem provides grounds for an explanation of the data presented above, and provides a framework within which we examine the role of various other factors in promoting the salience of a clausally introduced entity, including the information structure of the utterance in which the entity is introduced. For entities introduced by clausal complements to bridge verbs, we show that the information structure of the utterance introducing the entity has a partial, or one-sided, effect on the salience of the entity. When the complement clause is focal, the salience of the entity depends only on its referential givenness-newness (in the sense of Gundel 1988, 1999b), as we would expect. But when the complement clause is ground material, the salience of an entity introduced by the clause is enhanced. Other factors, including the presuppositionality of factive and interrogative complements, also serve to enhance the salience of entities introduced by complement clauses.