Investing in Emerging and Frontier Economies: How Blended Finance can make the most of public funding

Combating climate change and achieving the SDGs require vast investment in sustainable projects in developing countries, but the world is falling short.A crucial reason is that a rich source of funds is not being fully tapped into: the private sector, which is eager to significantly increase its sustainable investments, but is constrained by avoidable obstacles.Private investors face an unattractive risk-return nexus; they lack easy access to crucial information: e.g. which projects the public sector is planning that they could take part in, and what they entail.Exposure to the risks of investing in less mature markets, with insufficient insurance available, deters them as well.In this report, the Investor Leadership Network (ILN), whose members manage over USD 9 trillion of investments, offers solutions.It calls for better collaboration between public and private sectors to make blended finance (public/private investment partnerships) a driving force in this area.Compiled with the support of The Rockefeller Foundation, the report calls for a sea change in how multilateral development banks (MDBs), governments, foundations, and other public institutions see private-sector involvement

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe