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Interesting discussion of evidence on what does, and does not, work in tackling gender bias in recruitment and management processes. Evidence shows that skills-based assessment tasks (where candidates are given tests that replicate the work they'll actually do on the job) and structured interviews (where all candidates are given the same questions in the same order) have a positive impact on diverse recruitment. Unstructured interviews are more likely to allow unfair bias to creep in. Making promotion and pay processes more transparent can reduce pay inequality: when decisions are reviewed by others, managers realise they need to be objective and evidence-based. Evidence also shows women ask for less money than men. To encourage them to negotiate more, employers should make the possible salary range for roles clear. Studies indicate that women are put off negotiating when they're not sure what a reasonable offer is. "A lot of employers are genuinely really keen to reduce the gender pay gap, and also want to show they're making a change. But they're starved for information about what is likely to work,"

The Supreme Court does not compute. Or at least some of its members would rather not. The justices, the most powerful jurists in the land, seem to have a reluctance - even an allergy - to taking math and statistics seriously. For decades, the court has struggled with quantitative evidence of all kinds in a wide variety of cases. Sometimes justices ignore this evidence. Sometimes they misinterpret it. And sometimes they cast it aside in order to hold on to more traditional legal arguments. (And, yes, sometimes they also listen to the numbers.) Yet the world itself is becoming more computationally driven, and some of those computations will need to be adjudicated before long. Some major artificial intelligence case will likely come across the court's desk in the next decade, for example. By voicing an unwillingness to engage with data-driven empiricism, justices - and thus the court - are at risk of making decisions without fully grappling with the evidence. This problem was on full display earlier this month, when the Supreme Court heard arguments in Gill v. Whitford, a case that will determine the future of partisan gerrymandering - and the contours of American democracy along with it. As my colleague Galen Druke has reported, the case hinges on math: Is there a way to measure a map's partisan bias and to create a standard for when a gerrymandered map infringes on voters' rights?

Ocean acidification is an inevitable consequence of increasing carbon dioxide in the atmosphere. That's a matter of fact. We don't know exactly what will happen to complex marine ecosystems when faced with the additional stress of falling pH, but we do know those changes are happening and that they won't be good news.Freedom of speech, and of the press, is, of course, precious. Yet that freedom also brings responsibility. The Editors' Code of Practice - which IPSO says it upholds - requires the "highest professional standards". This includes taking care not to publish inaccurate, misleading or distorted information or images, including headlines not supported by the text. In addition, a significant inaccuracy, misleading statement or distortion must be corrected, promptly and with due prominence, and - where appropriate - an apology published.Is this just an honest opinion, a statement of fact or wilfully misleading and clever rhetoric? That depends on what is meant by "evidence". If it means quality research carried out by scientists with expertise in the field, the statement is factually incorrect. But if evidence includes anything said by non-experts, such as Delingpole, then that's an increase, right?

A good example of poor reporting of a medical study, the Daily Mail claimed that "Diets laden with butter, cream and cheese 'can help combat surge in type 2 diabetes' - but the evidence does not support that argument - looking at the evidence, it's clear there is a small quantifiable difference between the two groups analysed, and that the study focuses on a short period of time.

Medicine's decades-long march toward patient autonomy means patients are often now asked to make the hard decisions - to weigh trade-offs, to grapple with how their values suggest one path over another. This is particularly true when medical science doesn't offer a clear answer: Doctors encourage patients to decide where evidence is weak, while making strong recommendations when evidence is robust. But should we be doing the opposite?People in general are not great at evaluating risk. They worry more about shark attacks than car crashes.

So I set out to get to the bottom of the evidence on how we respond to rational arguments. Does rationality lose out every time to irrational motivations? Or is there any hope to those of us who want to persuade because we have good arguments, not because we are handsome, or popular, or offer heavy clipboards.

Everyone makes claims about what works. Politicians claim that stop-and-search policing will reduce violent crime; friends might assert that vaccines cause autism; advertisers declare that natural food is healthy. A group of scientists describes giving all schoolchildren deworming pills in some areas as one of the most potent anti-poverty interventions of our time. Another group counters that it does not improve children's health or performance at school. Unfortunately, people often fail to think critically about the trustworthiness of claims, including policymakers who weigh up those made by scientists. Schools do not do enough to prepare young people to think critically1. So many people struggle to assess evidence. As a consequence, they might make poor choices. To address this deficit, we present here a set of principles for assessing the trustworthiness of claims about what works, and for making informed choices (see 'Key Concepts for Informed Choices'). We hope that scientists and professionals in all fields will evaluate, use and comment on it.

How statistics, and research-design have changed the face of medicine. We tend to think of medicine as a science, but for most of human history it has been scientific-ish at best. In the first episode of a three-part series, we look at the grotesque mistakes produced by centuries of trial-and-error, and ask whether the new era of evidence-based medicine is the solution.

How are your intuitions shaped by the immediate world around you? The importance of evidence over anecdote and considering the bigger picture! If it's hot outside, you're more likely to believe in climate change. The public perception of climate change is shaped by the weather that people experience, according to a study published yesterday in the Proceedings of the National Academy of Sciences journal.

Have you ever noticed that when you present people with facts that are contrary to their deepest held beliefs they always change their minds? Me neither. In fact, people seem to double down on their beliefs in the teeth of overwhelming evidence against them. The reason is related to the worldview perceived to be under threat by the conflicting data.

This is a great list of evidence based stories by FiveThirtyEight (FiveThirtyEight uses statistical analysis - hard numbers - to tell compelling stories about elections, politics, sports, science, economics) They also produced a list of some great stories from other venues: http://fivethirtyeight.com/features/damn-we-wish-wed-written-these-11-stories/

Read the comments alongside the article here - interesting speculation and use of evidence. initiatives will not turn the affordability problem around while tax settings continue to support existing homeowners and investors at the expense of first time buyers and renters. Moreover, apart from a brief interruption 2008-2012, the Commonwealth has been steadily winding back its explicit housing role for more than 20 years. The post of housing minister was deleted in 2013, and just last month Government senators dismissed calls for renewed Commonwealth housing policy leadership recommended by the Senate's extensive (2013-2015) Affordable Housing Inquiry. This complacency cannot go unchallenged.

Interesting perspective on communicating evidence. With controversy about science communication, facts and alternative facts hitting the headlines recently, I've been having a number of conversations with colleagues from all over the world about why science seems to be losing in the current war on reason. This isn't in the usual fringe battle fronts like creationism or flat-Earthers. It's on topics deep behind our lines, in areas like whether climate change exists or not, how many people were present at a given time at a given place and whether one man with a questionable grasp on reality should be the only source people get their news from.

just knowing facts doesn't necessarily guarantee that one's opinions and behaviors will be consistent with them. For example, many people "know" that recycling is beneficial but still throw plastic bottles in the trash. Or they read an online article by a scientist about the necessity of vaccines, but leave comments expressing outrage that doctors are trying to further a pro-vaccine agenda. Convincing people that scientific evidence has merit and should guide behavior may be the greatest science communication challenge, particularly in our "post-truth" era. Luckily, we know a lot about human psychology - how people perceive, reason and learn about the world - and many lessons from psychology can be applied to science communication endeavors.

Not so much about data, but about how we use evidence when we don't know the original source, and how e e.g. a politician failing to deny something might be good confirmation that it's actually true. 5 tips for reading stories with unnamed sources

How do we know what we don't know? How do some people use ignorance, or claim ignorance, to mislead (e.g., by claiming that we are ignorant of the causes of climate change)? How do we navigate claims when two sides are in direct opposition? Radio national discuss the study of ignorance, and how it relates to evidence and arguments

There's a huge debate going on in social science right now. The question is simple, and strikes near the heart of all research: What counts as solid evidence? The answer matters because many disciplines are currently in the midst of a "replication crisis" where even textbook studies aren't holding up against rigorous retesting. ...

It's human nature to spot patterns in data. But we should be careful about finding causal links where none may existStories about people getting blood clots soon after taking the Oxford/AstraZeneca vaccine have become a source of anxiety among European leaders. After a report on a death and three hospitalisations in Norway, which found serious blood clotting in adults who had received the vaccine, Ireland has temporarily suspended the jab. Some anxiety about a new vaccine is understandable, and any suspected reactions should be investigated. But in the current circumstances we need to think slow as well as fast, and resist drawing causal links between events where none may exist.

The argument is simple, and goes a bit like this. Science does not work by appeal to authority, but rather by the acquisition of experimentally verifiable evidence. Appeals to scientific bodies are appeals to authority, so should be rejected. ...If legitimate authorities are not to be consulted, presumably there is no point in having scientists around at all, as each person would need to verify any claim on their own terms and with their own resources. That would mean a speedy decline into very dark times indeed.

"we pushed back against a misleading news release from Yale University that ran with the headline, "Yale researchers discover underlying cause of myeloma." The release claimed that the researchers identified "what causes a third of all myelomas," describing a faulty immune system response to compounds known as lysolipids as the culprit. But that characterization was wrong. First off, the research only demonstrated an association between lysolipids and this cancer - they didn't prove that one caused the other. And far from applying to a third of myeloma patients, the findings applied only to a tiny group of patients "