Phenomenological researchers say "capta" is the "data of the conscious experience." Is there room for this kind of data in analytics? How should analytics pros use it?

Bryan Beverly, Statistician, Bureau of Labor Statistics

August 16, 2017

3 Min Read
<p>(Image: Carlos Amarillo/Shutterstock)</p>

Ever heard of phenomenology? Phenomenology is the study of the structures of experience and consciousness; it is an attempt to give direct descriptions of human experiences. It challenges the assumptions of positivism or naturalistic empiricism, that scientists can directly investigate the world around them, record the findings, and build upon a body of knowledge that explains or predicts events in an objective manner.

Phenomenology is not a clearly defined body of teachings, rather it is more of a movement, whose trajectory has gone in several directions. Hence, even its definition is somewhat subjective. Its units of analysis include, but are not limited to human intentions, intuitions, and empathy. Its interpretive frames of reference include, but are not limited to existentialism, (the process of defining one's identity), semiotics (the study of signs and symbols with commonly understood meanings) and hermeneutics (the study of methods of textual interpretation). Therefore, using customized and commonly shared understandings, phenomenology explores all avenues of what it means to be human.

In terms of its assumptions, phenomenology: (1) rejects the concept of objective research, (2) posits that human behavior should be interpreted subjectively, and (3) uses methods that are discovery-oriented vis-à-vis methods that seek explanations or make predictions.

The aim of phenomenological research is to acquire data; the term used to define this data is called 'capta'. Capta is not data as we typically understand data. Capta represents what is seen, thought and felt. Capta, according to phenomenologists, is the 'data of the conscious experience'.

Obviously capta as a data type is atypical at best, and creates a plethora of challenges for traditional analytics. For example, the decennial Census may code your gender in two discrete categories. But one's gender identity and associated experiences may be more fluid, continuous, and dynamic. In fact, almost any of the demographic questions on the Census could be in a state of discovery or reimagining. Irrespective of one's skills, knowledge, and abilities, it is hard to translate conscious experience into SAS code.

Because capta represents the conscious experience, five analytical 'problems' (problems for traditional analysts) arise. First, can you define the data? Can one always translate an experience into words? Second, is the data accessible? Is there a willingness to open up and be transparent, exposed, and vulnerable? Third, will the data be understood by those who have not had this same experience? Fourth, will the data be believable? Fifth, even if the capta is defined, accessible, understood, and believed, is it analytically useful and usable? Does one know which tools are best suited for analyzing elements of the conscious experience? And what does one do with the results? Can one use data from personal experiences to shape public policy?

Whether this is your first or five hundredth exposure to phenomenology and capta, you can easily see why this topic does not receive much analytic attention -- if any. As analytic professionals, we are built for handling data that fosters explanations and predictions. But data related to uncovering the conscious experience? That is a whole different ball game. So what are your thoughts about subjective analytics? Can we make it amenable to traditional number crunching? If we record capta as statements, can we then use text mining to understand the conscious experience? 

About the Author(s)

Bryan Beverly

Statistician, Bureau of Labor Statistics

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