In March 2018, Mario Luis Small gave a public lecture at Columbia University on “Rhetoric and Evidence in a Polarized Society.” In this terrific must-read speech, Small asserts that today’s public discourse concerning society’s most deserving issues – poverty, inequality, and economic opportunity – has been seriously weakened by the absence of “qualitative literacy.” Qualitative literacy has to do with “the ability to understand, handle, and properly interpret qualitative evidence” such as ethnographic and in-depth interview (IDI) data. Small contrasts the general lack of qualitative literacy with the “remarkable improvement” in “quantitative literacy” particularly among those in the media where data-driven journalism is on the rise, published stories are written with a greater knowledge of quantitative data and use of terminology (e.g., the inclusion of means and medians), and more care is given to the quantitative evidence cited in media commentary (i.e., op-eds).
Small explains that the extent to which a researcher (or journalist or anyone involved in the use of research) possesses qualitative literacy can be determined by looking at the person’s ability to “assess whether the ethnographer has collected and evaluated fieldnote data properly, or the interviewer has conducted interviews effectively and analyzed the transcripts properly.” This determination serves as the backbone of “basic qualitative literacy” which enables the research user to identify the difference between a rigorous qualitative study and Read Full Text
Researchers of all ilk care about bias and how it may creep into their research designs resulting in measurement error. This is true among quantitative researchers as well as among qualitative researchers who routinely demonstrate their sensitivity to potential bias in their data by way of building interviewer training, careful recruitment screening, and appropriate modes into their research designs. It is these types of measures that acknowledge qualitative researchers’ concerns about quality data; and yet, there are many other ways to mitigate bias in qualitative research that are often overlooked.
Marketing researchers (and marketing clients) in particular could benefit from thinking more deeply about bias and measurement error. In the interest of “faster, cheaper, better” research solutions, marketing researchers often lose sight of quality design issues, not the least of which concern bias and measurement error in the data. If marketing researchers care enough about mitigating bias to train interviewers/moderators, develop screening questions that effectively target the appropriate participant, and carefully select the suitable mode for the population segment, then it is sensible to adopt broader design standards that more fully embrace the collecting of quality data.
An example of a tool that serves to raise the design standard is the reflexive journal. The reflexive journal has been the subject (in whole or in part) of many articles in Research Design Review, most notably Read Full Text
Janette Brocklesby recently wrote an article in QRCA Views magazine concerning the conduct of qualitative research with the Māori population of New Zealand. Specifically, she addresses the issue of whether “non- Māori researchers have the cultural competency, expertise and skills to undertake research with Māori.” Brocklesby makes the case in the affirmative, emphasizing that non- Māori qualitative researchers are “well equipped to undertake research with Māori and to convey the Māori perspective.”
In making her case, Brocklesby discusses many of the best practices mentioned repeatedly in Research Design Review. As for all qualitative research, a researcher studying Māori groups must place a high importance on:
Reflexivity – Continually questioning and contemplating the researcher’s role or impact on research outcomes is a critical step towards quality results. In March 2014, an article in RDR talked about using a reflexive journal to think about the assumptions, values, and beliefs Read Full Text