Five-year campaign breaks science’s citation paywall

Curated on Posted on by Stefaan Verhulst

Article by Dalmeet Singh Chawla: “The more than 60 million scientific-journal papers indexed by Crossref — the database that registers DOIs, or digital object identifiers, for many of the world’s academic publications — now contain reference lists that are free to access and reuse.

The milestone, announced on Twitter on 18 August, is the result of an effort by the Initiative for Open Citations (I4OC), launched in 2017. Open-science advocates have for years campaigned to make papers’ citation data accessible under liberal copyright licences so that they can be studied, and those analyses shared. Free access to citations enables researchers to identify research trends, lets them conduct studies on which areas of research need funding, and helps them to spot when scientists are manipulating citation counts….

The move means that bibliometricians, scientometricians and information scientists will be able to reuse citation data in any way they please under the most liberal copyright licence, called CC0. This, in turn, allows other researchers to build on their work.

Before I4OC, researchers generally had to obtain permission to access data from major scholarly databases such as Web of Science and Scopus, and weren’t able to share the samples.

However, the opening up of Crossref articles’ citations doesn’t mean that all the world’s scholarly content now has open references. Although most major international academic publishers, including Elsevier, Springer Nature (which publishes Nature) and Taylor & Francis, index their papers on Crossref, some do not. These often include regional and non-English-language publications.

I4OC co-founder Dario Taraborelli, who is science programme officer at the Chan Zuckerberg Initiative and based in San Francisco, California, says that the next challenge will be to encourage publishers who don’t already deposit reference data in Crossref to do so….(More)”.

Uncovering the genetic basis of mental illness requires data and tools that aren’t just based on white people

Curated on Posted on by Stefaan Verhulst

Article by Hailiang Huang: “Mental illness is a growing public health problem. In 2019, an estimated 1 in 8 people around the world were affected by mental disorders like depression, schizophrenia or bipolar disorder. While scientists have long known that many of these disorders run in families, their genetic basis isn’t entirely clear. One reason why is that the majority of existing genetic data used in research is overwhelmingly from white people.

In 2003, the Human Genome Project generated the first “reference genome” of human DNA from a combination of samples donated by upstate New Yorkers, all of whom were of European ancestry. Researchers across many biomedical fields still use this reference genome in their work. But it doesn’t provide a complete picture of human genetics. Someone with a different genetic ancestry will have a number of variations in their DNA that aren’t captured by the reference sequence.

When most of the world’s ancestries are not represented in genomic data sets, studies won’t be able to provide a true representation of how diseases manifest across all of humanity. Despite this, ancestral diversity in genetic analyses hasn’t improved in the two decades since the Human Genome Project announced its first results. As of June 2021, over 80% of genetic studies have been conducted on people of European descent. Less than 2% have included people of African descent, even though these individuals have the most genetic variation of all human populations.

To uncover the genetic factors driving mental illness, I, Sinéad Chapman and our colleagues at the Broad Institute of MIT and Harvard have partnered with collaborators around the world to launch Stanley Global, an initiative that seeks to collect a more diverse range of genetic samples from beyond the U.S. and Northern Europe, and train the next generation of researchers around the world. Not only does the genetic data lack diversity, but so do the tools and techniques scientists use to sequence and analyze human genomes. So we are implementing a new sequencing technology that addresses the inadequacies of previous approaches that don’t account for the genetic diversity of global populations…(More).

Income Inequality Is Rising. Are We Even Measuring It Correctly?

Curated on Posted on by Stefaan Verhulst

Article by Jon Jachimowicz et al: “Income inequality is on the rise in many countries around the world, according to the United Nations. What’s more, disparities in global income were exacerbated by the COVID-19 pandemic, with some countries facing greater economic losses than others.

Policymakers are increasingly focusing on finding ways to reduce inequality to create a more just and equal society for all. In making decisions on how to best intervene, policymakers commonly rely on the Gini coefficient, a statistical measure of resource distribution, including wealth and income levels, within a population. The Gini coefficient measures perfect equality as zero and maximum inequality as one, with higher numbers indicating a greater concentration of resources in the hands of a few.

This measure has long dominated our understanding (pdf) of what inequality means, largely because this metric is used by governments around the world, is released by statistics bureaus in multiple countries, and is commonly discussed in news media and policy discussions alike.

In our paper, recently published in Nature Human Behaviour, we argue that researchers and policymakers rely too heavily on the Gini coefficient—and that by broadening our understanding of how we measure inequality, we can both uncover its impact and intervene to more effectively correct It…(More)”.

The Low Threshold for Face Recognition in New Delhi

Curated on Posted on by Stefaan Verhulst

Article by Varsha Bansal: “Indian law enforcement is starting to place huge importance on facial recognition technology. Delhi police, looking into identifying people involved in civil unrest in northern India in the past few years, said that they would consider 80 percent accuracy and above as a “positive” match, according to documents obtained by the Internet Freedom Foundation through a public records request.

Facial recognition’s arrival in India’s capital region marks the expansion of Indian law enforcement officials using facial recognition data as evidence for potential prosecution, ringing alarm bells among privacy and civil liberties experts. There are also concerns about the 80 percent accuracy threshold, which critics say is arbitrary and far too low, given the potential consequences for those marked as a match. India’s lack of a comprehensive data protection law makes matters even more concerning.

The documents further state that even if a match is under 80 percent, it would be considered a “false positive” rather than a negative, which would make that individual “subject to due verification with other corroborative evidence.”

“This means that even though facial recognition is not giving them the result that they themselves have decided is the threshold, they will continue to investigate,” says Anushka Jain, associate policy counsel for surveillance and technology with the IFF, who filed for this information. “This could lead to harassment of the individual just because the technology is saying that they look similar to the person the police are looking for.” She added that this move by the Delhi Police could also result in harassment of people from communities that have been historically targeted by law enforcement officials…(More)”

Blue Spoons: Sparking Communication About Appropriate Technology Use

Curated on Posted on by Stefaan Verhulst

Paper by Arun G. Chandrasekhar, Esther Duflo, Michael Kremer, João F. Pugliese, Jonathan Robinson & Frank Schilbach: “An enduring puzzle regarding technology adoption in developing countries is that new technologies often diffuse slowly through the social network. Two of the key predictions of the canonical epidemiological model of technology diffusion are that forums to share information and higher returns to technology should both spur social transmission. We design a large-scale experiment to test these predictions among farmers in Western Kenya, and we fail to find support for either. However, in the same context, we introduce a technology that diffuses very fast: a simple kitchen spoon (painted in blue) to measure out how much fertilizer to use. We develop a model that explains both the failure of the standard approaches and the surprising success of this new technology. The core idea of the model is that not all information is reliable, and farmers are reluctant to develop a reputation of passing along false information. The model and data suggest that there is value in developing simple, transparent technologies to facilitate communication…(More)”.

Spirals of Delusion: How AI Distorts Decision-Making and Makes Dictators More Dangerous

Curated on Posted on by Stefaan Verhulst

Essay by Henry Farrell, Abraham Newman, and Jeremy Wallace: “In policy circles, discussions about artificial intelligence invariably pit China against the United States in a race for technological supremacy. If the key resource is data, then China, with its billion-plus citizens and lax protections against state surveillance, seems destined to win. Kai-Fu Lee, a famous computer scientist, has claimed that data is the new oil, and China the new OPEC. If superior technology is what provides the edge, however, then the United States, with its world class university system and talented workforce, still has a chance to come out ahead. For either country, pundits assume that superiority in AI will lead naturally to broader economic and military superiority.

But thinking about AI in terms of a race for dominance misses the more fundamental ways in which AI is transforming global politics. AI will not transform the rivalry between powers so much as it will transform the rivals themselves. The United States is a democracy, whereas China is an authoritarian regime, and machine learning challenges each political system in its own way. The challenges to democracies such as the United States are all too visible. Machine learning may increase polarization—reengineering the online world to promote political division. It will certainly increase disinformation in the future, generating convincing fake speech at scale. The challenges to autocracies are more subtle but possibly more corrosive. Just as machine learning reflects and reinforces the divisions of democracy, it may confound autocracies, creating a false appearance of consensus and concealing underlying societal fissures until it is too late.

Early pioneers of AI, including the political scientist Herbert Simon, realized that AI technology has more in common with markets, bureaucracies, and political institutions than with simple engineering applications. Another pioneer of artificial intelligence, Norbert Wiener, described AI as a “cybernetic” system—one that can respond and adapt to feedback. Neither Simon nor Wiener anticipated how machine learning would dominate AI, but its evolution fits with their way of thinking. Facebook and Google use machine learning as the analytic engine of a self-correcting system, which continually updates its understanding of the data depending on whether its predictions succeed or fail. It is this loop between statistical analysis and feedback from the environment that has made machine learning such a formidable force…(More)”

Nowcasting daily population displacement in Ukraine through social media advertising data

Curated on Posted on by Stefaan Verhulst

Pre-Publication Paper by Douglas R. Leasure et al: “In times of crisis, real-time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022 forcibly displaced millions of people from their homes including nearly 6m refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged near real-time social media marketing data to estimate sub-national population sizes every day disaggregated by age and sex. Our metric of internal displacement estimated that 5.3m people had been internally displaced away from their baseline administrative region by March 14. Results revealed four distinct displacement patterns: large scale evacuations, refugee staging areas, internal areas of refuge, and irregular dynamics. While this innovative approach provided one of the only quantitative estimates of internal displacement in virtual real-time, we conclude by acknowledging risks and challenges for the future…(More)”.

State of Gender Data

Curated on Posted on by Stefaan Verhulst

Report by Data2X: “Gender data is fundamental to achieving gender equality and the Sustainable Development Goals. It helps identify inequalities, illuminate a path forward, and monitor global progress. As recognition of its importance has grown over the last decade, the availability of gender data—and its use in decision-making—has improved.

Yet overlapping crises, from the COVID-19 pandemic to climate change and conflict, have imperiled progress on gender equality and the Sustainable Development Goals. In 2022, UN Secretary General Antonio Gutierrez declared that the Sustainable Development Goals are in need of rescue. The 2022 SDG Gender Index by EM2030 found little progress on global gender equality between 2015 and 2020, and a recent assessment by UN Women demonstrates that more than one quarter of the indicators needed to measure progress on gender equality are “far or very far” from 2030 targets….The State of Gender Data is an evolving Data2X publication and digital experience designed to highlight global progress and spur action on gender data. Data2X will update the initiative annually, providing insight into a new dimension of gender data. For our initial launch, we focus on examining funding trends and highlighting promising solutions and key commitments….(More)”.

Citizen science in environmental and ecological sciences

Curated on Posted on by Stefaan Verhulst

Paper by Dilek Fraisl et al: “Citizen science is an increasingly acknowledged approach applied in many scientific domains, and particularly within the environmental and ecological sciences, in which non-professional participants contribute to data collection to advance scientific research. We present contributory citizen science as a valuable method to scientists and practitioners within the environmental and ecological sciences, focusing on the full life cycle of citizen science practice, from design to implementation, evaluation and data management. We highlight key issues in citizen science and how to address them, such as participant engagement and retention, data quality assurance and bias correction, as well as ethical considerations regarding data sharing. We also provide a range of examples to illustrate the diversity of applications, from biodiversity research and land cover assessment to forest health monitoring and marine pollution. The aspects of reproducibility and data sharing are considered, placing citizen science within an encompassing open science perspective. Finally, we discuss its limitations and challenges and present an outlook for the application of citizen science in multiple science domains…(More)”.

Academic freedom and democracy in African countries: the first study to track the connection

Curated on Posted on by Stefaan Verhulst

Article by Liisa Laakso: “There is growing interest in the state of academic freedom worldwide. A 1997 Unesco document defines it as the right of scholars to teach, discuss, research, publish, express opinions about systems and participate in academic bodies. Academic freedom is a cornerstone of education and knowledge.

Yet there is surprisingly little empirical research on the actual impact of academic freedom. Comparable measurements have also been scarce. It was only in 2020 that a worldwide index of academic freedom was launched by the Varieties of Democracy database, V-Dem, in collaboration with the Scholars at Risk Network….

My research has been on the political science discipline in African universities and its role in political developments on the continent. As part of this project, I have investigated the impact of academic freedom in the post-Cold War democratic transitions in Africa.

A study I published with the Tunisian economist Hajer Kratou showed that academic freedom has a significant positive effect on democracy, when democracy is measured by indicators such as the quality of elections and executive accountability.

However, the time factor is significant. Countries with high levels of academic freedom before and at the time of their democratic transition showed high levels of democracy even 5, 10 and 15 years later. In contrast, the political situation was more likely to deteriorate in countries where academic freedom was restricted at the time of transition. The impact of academic freedom was greatest in low-income countries….(More)”