Evaluating the Accuracy of Reported Information

Dr. Sylvain Ehrenfeld, IHEU and National Ethical Service representative to the UN
Dr. Reba Goodman, member of ECSBC

We are inundated by information. One example of information overload is the stream of US election polls as if we are following a horse race. The Word Bank, the World Health Organization (WHO), and numerous UN agencies provide information regarding poverty, hunger in the world, access to clean water and sanitation, as well as the incidence of malaria. A look at The New York Times any day will provide endless information. On a single day they reported that 300 million people in India live without electricity and that India’s annual per capita carbon dioxide emission is 1.7 tons. What can we do with this information? Are the election polls useful? How do they affect the electorate?

Importantly: how accurate is all this information? Governments have been collecting data on their citizens for many centuries. The Egyptian Pharaohs conducted a census to find out the available labor force to build the pyramids and in the Roman Empire the five-yearly census was all about finding out who was available for military service and what wealth existed to be taxed. The ancient Babylonians collected data from their citizens nearly 6,000 years ago to understand how much food was required to feed their population. In the Bible it says that Moses counted males who have reached the age of 20 and are able to bear arms. As a result of current interest, let’s examine election polls and data from some UN agencies.

Most election polls depend on random sampling. More or less accurately, a random sample presents a snapshot representing the whole population from which it was drawn at one point in time. Polls are getting more difficult to do. In the past, data was collected automatically dialing telephone numbers on landlines—using repeated calls if necessary to minimize missing respondents. Today the response rates are way down to about ten percent, and those that do respond may not be representative. Furthermore, currently about 40 percent of the population has only cell phones—with no landline. So, some sampling must be done on cell phones—but US federal law prohibits automated dialing devices to call cell phones. Cell phone numbers have to be dialed by hand which is more time consuming and more expensive.

Households that use only cell phones tend to include minorities and younger voters and occur more frequently in Metropolitan areas. Men are more likely than women to be cell phone users. How to take such factors into account in the sampling? The best public pollsters use various “weighting” methods to take such variables into account in reported results. Other difficulties in polling include the effect of the wording of questions and the truthfulness of people’s responses. Polling has had accuracies as well as inaccuracies. A famous case was the Literary Digest poll in the 1936 presidential election between Roosevelt and Alf Landon. A random sample of telephone users was chosen. The result of the poll was a prediction of victory for Landon. Of course, Roosevelt won. The reason for the incorrect result was that telephone households were then more Republican than Democrats.

Another failure was the presidential election in 1948. Major polling organizations predicted a landslide victory for Dewey. Truman won the election. Some may remember a picture of Truman with a big smile holding up a newspaper with the headline that Dewey won. The cause of the wrong prediction was that pollsters stopped taking “snapshots” of the electorate too early before election day.

More recently, in the 2015 election in Britain pollsters missed the result of the win by the Conservatives. Also in 2015 polls in Israel failed to predict the victory of Benjamin Netanyahu.

It is not clear how polls influence voters and politicians. We think polls have a negative effect. Instead of concentrating on serious issues it tends to enhance the popularity contest. In 2015 the UN General Assembly voted to extend the Millennium Goals to the Sustainable Development Goals for the next 15 years. It consists of ambitious goals such as eliminating crushing poverty; hunger, providing clean water and sanitation, improving maternal health and climate action. Development goals require reliable indicators, must be measurable so that progress can be monitored. However, most of what we think of as facts are actually estimates.

We know less than we think we do. Around 1.2 billion people live in extreme poverty: maybe or maybe not. According to WHO malaria deaths fell by 49% in Africa between 2000 and 2013. Perhaps. Maternal mortality in Africa fell from 740 deaths per 100,000 live births in 2000 to 500 per 100,000 in 2010. We are not sure. We have actual numbers on maternal mortality for just 16% of all births and on malaria for about 15% of all deaths. For six countries in Africa, there is basically no information at all.

According to WHO more than two thirds of the world’s population lives in countries that do not produce reliable statistics on mortality by age, sex and cause of death. WHO is perfectly aware of the inadequacy of available data. What is much needed is support for countries to have strong health information systems. Without good data we are working in the dark. Bad data is a recipe for bad decisions. Governments and agencies need reliable data to know where to put their money and effort. They also need to know if what they are doing is actually working.

The UN is very much aware of the need for improved data and has called for a ‘Data Revolution’. An independent Expert Advisory Group of over 20 international experts have proposed methods to improve data collection. Their report “A World That Counts” has many suggestions for how to proceed. It will require increased funding. It is our opinion that people in their own locality must be helped and trained to establish and monitor the gathering of necessary Data.

A timely quote from Artimus Ward, “It ain’t so much the things we don’t know that gets us into trouble. It’s the things we know that ain’t so.”

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