Speaking truth to power about qualitative research

From a rejection letter to a qual researcher, about why the manuscript was being rejected:

BMJ review: Sorry but qualitative studies are an extremely low priority Our research shows they are not widely accessed, downloaded or cited

— MQHRG (@mqhrg) September 30, 2015

Of course, the whining and outrage was predictable. More here:

https://storify.com/shereebekker/bmjnoqual

Let’s face facts: it’s a quant world now. Policymakers and stakeholders don’t want to hear stories about the lived experience or any other such nonsense. Funders are increasingly adopting a similar mindset.

The trend is only going to get worse:

1. Statistics is now prominent in the K-12 math curriculum; it was nonexistent when I was a kid. Students at a young age will now be learning quant methods, not qual methods.
2. The media has gotten much more data savvy, and now regularly present charts and graphs based on quant data. This is creating a culture where we tend to talk and view issues in terms of what the quant data tell us.
3. Number 2 is especially true for academic research. The Chronicle of Higher Ed and Inside Higher Ed report predominantly on quant studies. The major media outlets, like the NY Times, tend to report on work done by economists. When was the last time you read about an anthropological study in the national media?
4. More and different quant datasets are continually collected, as we use more electronic devices and the cost of data storage continues to drop to almost nothing. So it’s becoming much easier to study a wide variety of topics using a quant lens than it was 20 or even 10 years ago.
5. Statistical and visualization software is easier to use every year, putting more tools in the hands of people who might normally never crack open R and run a regression analysis.

Qual folks are also their single best enemy. I trained in comparative politics, where qual scholars are respected, because they adopt a case study approach. Many of the qual researchers I see in education and other areas tend to do dumb things like:

1. Abandon any approach to representative sampling when they select participants. They refer this as “purposive sampling” but it is often just an excuse for laziness – representative samples require a lot of work to collect. In a world where K-12 students are now being trained in the nuances of populations and samples, how do you think the average person, or policymaker, reacts to your study when you admit that the people you interviewed are not representative of anything?
2. Some qual researchers insist there are multiple realities. What do you think the average person, who lives in a single reality like most of us, thinks of this idea?
3. Some are also opposed to any notion of causality and reject the entire concept. Yet we live in a time when voters and policymakers are desperate for solutions to society’s problems. Do you honestly think they want to hear from someone who says, “Sorry, but I can’t really say whether smaller class size causes students’ test scores to increase. I can only describe the students’ experiences”? Such an approach is not very helpful to school districts trying to decide between hiring more teachers versus increasing teacher compensation.

In short, the future of qual research looks grim. When policymakers ignore your research, funders decline to fund it, reporters don’t write about it, and publishers tracking downloads begin to reject it, you are clearly a dinosaur. The comet has hit; you just don’t realize it yet.

FYI, in response to the brouhaha, the International Journal of Qual Methods has published an editorial giving tips for qual researchers on how to get published in good journals. They have good advice for any researcher, qual or quant:

http://ijq.sagepub.com/content/15/1/1609406916641250.full