The Total Quality Framework (TQF) is rooted in the idea that a quality approach to qualitative research requires “quality thinking” at each stage of the research process. It is an idea derived from the logic that it is not good enough to think carefully about data collection without also thinking as carefully about the analysis and reporting phases while keeping a discerning eye on the ultimate goal of gaining useful research results. This fundamental concept underlies the TQF and serves to define its four components – Credibility (pertaining to the data collection phase), Analyzability (analysis), and Transparency (reporting), and Usefulness (being able to do something of value with the outcomes).
By considering quality standards at each step in the research design, qualitative researchers maintain the integrity of their data through the entire study thereby producing something of value to the users of their research. For instance, a concerted quality approach to data collection – an approach that mitigates researcher bias and gathers valid data – but a disregard for the quality process in the analysis phase – e.g., transcripts are poorly done, coding is inconsistent, and verification of the data is absent – weakens the entire study. Likewise, a deliberate quality approach to data collection and analysis but a failure to write a transparent final document that reveals the details of the study’s scope, data gathering, analysis process and verification, effectively masks the integrity of the research and undermines its critical value to users.
A holistic quality-centric approach to qualitative research design essentially means that a weakness in any one link in the quality chain – the chain from data collection to analysis to reporting – erodes the purpose of conducting qualitative research (regardless of method) which is to offer useful information by way of new hypotheses, next steps, and/or applications to other contexts.
In qualitative research, the researcher – including the in-depth interviewer, focus group moderator, coder in content analysis, and observer – is the instrument, meaning that the qualitative researcher wields substantial control in the design content, the gathering of data, the outcomes, and interpretation of the research. Ethnography is no different in that the observer – albeit not controlling participants’ natural environment – plays a central role in creating the data for the study by way of recording observations. In this respect, the credibility of an ethnographic study essentially rests on the observer’s ability to identify and record the relevant observations.
The necessary observer skills have been discussed elsewhere in Research Design Review – for example, “The Importance of Analytical Sensibilities to Observation in Ethnography.” Without these skills, an observer has the potential for biasing the data which in turn will negatively impact the analysis, interpretation, transferability, and ultimate usefulness of an ethnographic study. The potential for bias exists regardless of observer role. An offsite, non-participant observer may knowingly or not impose subjective values on an observed event – e.g., ignoring certain comments the observer finds personally offensive in a study of an online forum discussing alcohol use – while an onsite observer, operating either overtly or covertly, may bias results by way of Read Full Text
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