UTS-AEI

When Uber and Lyft first entered the market, offering a ride-hailing service that would come to include tens of thousands of amateur drivers, most major American cities had been tightly controlling the competition. New York City allowed exactly 13,637 licenses for taxicabs. Chicago permitted 6,904, Boston 1,825 and Philadelphia 1,600. These numbers weren't entirely arbitrary. Cities had spent decades trying to set numbers that would keep drivers and passengers satisfied and streets safe. But the exercise was always a fraught one. And New York City now faces an even more complex version of it, after the passage of legislation this week that will temporarily cap services like Uber and Lyft. The city plans to halt new licenses for a year while it studies the impact of ride-hailing and establishes new rules for driver pay. In doing so, it renews an old question: What's the right number of vehicles anyway? The answer isn't easy because it depends largely on which problem officials are trying to solve. Do they want to minimize wait times for passengers or maximize wages for drivers? Do they want the best experience for individual users, or the best outcome for the city - including for residents who use city streets but never ride taxis or Uber at all?

Interesting look at data around private healthcare and marketisation. Each year, for well over a decade, more people have faced higher health insurance deductibles. The theory goes like this: The more of your own money that you have to spend on health care, the more careful you will be - buying only necessary care, purging waste from the system. But that theory doesn't fully mesh with reality: High deductibles aren't working as intended. A body of research - including randomized studies - shows that people do in fact cut back on care when they have to spend more for it. The problem is that they don't cut only wasteful care. They also forgo the necessary kind. This, too, is well documented, including with randomized studies. People don't know what care they need, which is why they consult doctors.

Why do arguments change people's minds in some cases and backfire in others? Hugo Mercier explains how arguments are more convincing when they rest on a good knowledge of the audience, taking into account what the audience believes, who they trust, and what they value.

In August 2016, the Australian government released an "anonymised" data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people. Names and other identifying features were removed from the records in an effort to protect individuals' privacy, but a research team from the University of Melbourne soon discovered that it was simple to re-identify people, and learn about their entire medical history without their consent, by comparing the dataset to other publicly available information, such as reports of celebrities having babies or athletes having surgeries.

People use imprecise words to describe the chance of events all the time - "It's likely to rain," or "There's a real possibility they'll launch before us," or "It's doubtful the nurses will strike." Not only are such probabilistic terms subjective, but they also can have widely different interpretations. One person's "pretty likely" is another's "far from certain." Our research shows just how broad these gaps in understanding can be and the types of problems that can flow from these differences in interpretation.

Nice discussion of the data around contraception choices. Shortly after Donald Trump was elected president I started noticing an interesting trend on my social media newsfeeds. And no, I'm not talking about the near-constant bickering of people with differing political opinions. I started seeing post after post from friends publicly asking one another about their experiences with different forms of birth control. The motivation for these kinds of conversations centered around the pending rollback of copay-free contraception, but have since been re-kindled every time reproductive rights come up in the political arena. And it's not just talk. Many of these conversations centered around the use of long-term contraceptives like intra-uterine devices or IUDs which can protect against pregnancy for 3 - 12 years. In the months immediately following the 2016 election, AthenaHealth reported a 19% increase in IUD-related doctor's visits and Planned Parenthood reported a 900% increase in patients seeking IUDs. Cait, 27, recently switched to a copper IUD, and said that she made the switch due to convenience and "because now in light of our current administration I'd like to have something that will continue to work and be affordable even if I end up without health insurance."

Two Words That Could Shape the Politics of the Trade War: Loss Aversion The pain of a loss tends to be greater than the enjoyment of a win. That has big implications for trade, and also helps explain the politics of health care and taxes.

Interesting discussion of why headlines like this one "85% accurate" for the detection of stomach cancer" about an experimental breath test are problematic (because some people who don't have the condition get diagnosed with it, and they can miss people who genuinely do have the condition!). Good example using pregnancy tests as an infographic.

journalists often write about public opinion polls, which are designed to measure the public's attitudes about an issue or idea. Some of the most high-profile polls center on elections and politics. Newsrooms tend to follow these polls closely to see which candidates are ahead, who's most likely to win and what issues voters feel most strongly about. Other polls also offer insights into how people think. For example, a government agency might commission a poll to get a sense of whether local voters would support a sales tax increase to help fund school construction. Researchers frequently conduct national polls to better understand how Americans feel about public policy topics such as gun control, immigration reform and decriminalizing drug use. When covering polls, it's important for journalists to try to gauge the quality of a poll and make sure claims made about the results actually match the data collected. Sometimes, pollsters overgeneralize or exaggerate their findings. Sometimes, flaws in the way they choose participants or collect data make it tough to tell what the results really mean. Below are 11 questions we suggest journalists ask before reporting on poll results. While most of this information probably won't make it into a story or broadcast, the answers will help journalists decide how to frame a poll's findings - or whether to cover them at all.

Last week, the American Cancer Society published new guidelines that call for colorectal cancer screening to begin at age 45 - five years earlier than the group had previously recommended. But some experts are saying not so fast. The new recommendation was made in reaction to increasing rates of colorectal cancer among people younger than 50. But while the rise in cancers among this younger age group is troubling, this new recommendation was made before we know what's behind the new trend. And it's not clear that screening can help.It makes intuitive sense to respond to increasing rates of colon cancer among young people by lowering the screening age, said Michael Hochman, director of the the Gehr Family Center for Health Systems Science at the Keck School of Medicine in Los Angeles. "But if I had a quarter for every time in medicine that we were tricked by an idea with intuitive appeal, I'd be a rich man," Hochman said.

Interesting article discussing how ai is being used in medical diagnoses

Great podcast from our own 2ser & UTS Business School! "latest episode of #ThinkBusinessFutures @2ser, with Dr Geetanjali Saluja @UTSMarketing @UTS_Business, discussing her research into moral decision making, and Adam Ferrier, author of 'The Advertising Effect: How to Change Behaviour'" Discusses some of the framing, cognitive bias, and their impact on decision making that we talked about in class

A great video example discussing a contentious issue (coal consumption) using the data!

The Guardian datablog has a set of visualisations https://www.theguardian.com/technology/data-visualisation and a set of stories focused on the Australian context; useful for exploring how data analysis and visusalisation are used to tell a story.

Really good video illustrating how (a) gathering data, and (b) understanding the shape of that data can give us insight onto real world issues, and help us to target approaches to tackling them "Britain has carried out one of the biggest data-gathering exercises on the gender pay gap, exposing large disparities between the average pay given to men and women in some of the country's best-known companies. We dispel some of the myths around the gap, and explain what it really means and why it matters"

Some fantastic visualisations in this piece from the Guardian, including a scatterplot and some different kinds of histograms! Well worth exploring. "The figures reveal men are paid more than women in 7,795 out of 10,016 companies and public bodies in Britain, based on the median hourly pay. Across the companies and organisations that had filed by 8am on Thursday, eight out of 10 had a gender pay gap. While the figures do not reflect equal pay for equal work, they do raise questions about structural inequalities in the workforce and may hold the answer to closing the gap."

Is income inequality growing (in America)? This article discusses the issue, and uses a chart from the Financial Times (and Pew research data) to demonstrate the change since 1971. Great visualisation and great discussion of what it shows.

An introduction to a set of deep dive articles an important issue....When we tell people that we work at the intersection of statistics and human rights, the reaction is often surprise. Everyone knows that lawyers and journalists think about human rights problems … but statisticians? Yet, documenting and proving human rights abuses frequently involves the need for quantification. In the case of war crimes and genocide, guilt or innocence can hinge on questions of whether violence was systematic and widespread or one group was targeted at a differential rate compared to others. Similar issues can arise in assessing violations of civil, social, and economic rights. Sometimes the questions can be answered through simple tabulations, but often, more-complex methods of data collection and analysis are required.

If you look at marathon times, you see most people run somewhere in the middle (4 hoursish), with a few under 3 hours (?!) and over 6 hours (very sensible). If you plot this data in a histogram, you can also see that there are spikes...people run just under 3, 3.5, 4, and 4.5 hours - you can see that people have a goal (of a nice round number) and the times are distributed accordingly.

Every year in Australia, the National Assessment Program - Literacy and Numeracy (NAPLAN) results show Indigenous school students are well behind their non-Indigenous peers. Reducing this disparity is a vital part of Australia's national Closing the Gap policy. ... Using an updated version of our equivalent year levels metric, introduced in Grattan Institute's 2016 report Widening Gaps, we estimate year nine Indigenous students in very remote areas are: five years behind in numeracy six years behind in reading, and seven to eight years behind in writing. In other words, the average year nine Indigenous student in a very remote area scores about the same in NAPLAN reading as the average year three non-Indigenous city student, and significantly lower in writing. But it would be a big mistake to see this only as a problem for isolated outback communities. Most Indigenous students live in cities or regional areas. So, even though learning outcomes are worse in remote and very remote areas, city and regional students account for more than two-thirds of the lost years of learning.