Chapter Summary
This chapter illustrates methods for organizing condensed qualitative data, from highly systematic to artistically rendered ways, for purposes of descriptive documentation. The descriptive profiles focus on describing participants, variability, and social action.
Contents
Introduction
Describing Participants Role-Ordered Matrix Context Chart
Describing Variability Construct Table
Conceptually Clustered Matrix Folk Taxonomy
Describing Action Vignettes
Poetic Display Cognitive Maps Closure and Transition
Introduction
Wolcott (1994) advocates that description is qualitative representation that helps the reader see what you saw and hear what you heard. A solid, descriptive foundation of your data enables higher level analysis and interpretation. Usually, it is hard to explain the “hows” and “whys” of something satisfactorily until you understand just what that something is.
You begin with a text, trying out codes on it, then moving to identify patterns, categories, or themes, and then to testing hunches and findings, aiming first to delineate the “deep structure” and then to integrate the data into an explanatory framework. In this sense, we can speak of data transformation as information that is condensed, clustered, sorted, and linked over time. The researcher typically moves through a series of analysis episodes that condense more and more data into a more and more coherent understanding of what—building a solid foundation for later analyzing how and why (Wolcott, 1994).
Describing Participants looks at the relationship dynamics of the people you study. Describing Variability charts the spectrum and landscape of what we’re finding in the field. And Describing Action documents the experiences and processes of our participants from systematic to artistically rendered ways.
Describing Participants
The role-ordered matrix charts the essential characteristics relevant to the study of the various participants. A context chart illustrates the hierarchies and interrelationships within, between, and
among the participants.
Role-Ordered Matrix Description
A role-ordered matrix sorts data in its rows and columns that have been gathered from or about a certain set of “role occupants”—data reflecting their views. The display systematically permits comparisons across roles on issues of interest to a study and tests whether people in the same role see issues in comparable ways (see Display 7.1).
Applications
People who live in groups and organizations, like most of us, and social scientists who study groups and organizations know that how you see life depends, in part, on your role. A role is a complex amalgam of expectations and actions that make up what you do, and should do, as a certain type of actor in a setting—a family, a classroom, a committee, a hospital, a police department, or a multinational corporation.
A role-ordered matrix groups, summarizes, and compares different people’s role perceptions about selected topics or issues that enable the researcher to compare and contrast those perceptions.
For example, mothers tend to see the world differently than fathers. Bosses tend not to see the frustrations faced by workers, partly because they are distant from them and partly because subordinates often censor the bad news when reporting upward. A teacher’s high-speed interactions with several hundred children over the course of a day have a very different cast to them from the principal’s diverse transactions with parents, vendors, secretaries, central office administrators, and other teachers. We each experience the world differently, and a role-ordered matrix is just one way of documenting those varied experiences.
Example
We (Miles and Huberman) draw on our school improvement study for an example. The innovation involved is an intensive remedial program, implemented in a high school, emphasizing reading in the subjects of English, science, and math. The question of interest is “How do people react to an innovation when they first encounter it?” This general question can be unbundled into several subquestions, such as the following:
• Which aspects of the innovation are salient and stand out in people’s minds?
• How do people size up the innovation in relation to its eventual implementation?
• What changes—at the classroom or organizational level—do people think the innovation will require?
• How good a fit is the innovation to people’s previous classroom styles or to previous organizational working arrangements?
Keeping in mind that we want to see answers to these questions broken out by different roles, we can consider which roles—for example, teachers, department chairs, principals, central office personnel—could be expected to attend to the innovation and could provide meaningful reactions to it. The matrix rows could be roles, but if we want to make within-role comparisons, the rows should probably be persons and clustered into role domains. It might be good, too, to order the roles according to how far they are from the actual locus of the innovation—from teachers to central office administrators. The columns can be devoted to the research subquestions. Display 7.1 shows how this approach looks.
The researcher searches through coded write-ups for relevant data, and the data entered in each cell are a brief summary of what the analyst found for each respondent. The main decision rule was as follows: If it’s in the notes, and not internally contradicted, summarize it and enter a phrase
reflecting the summary. There are also “DK” (“don’t know”) entries, where data are missing because the relevant question was never asked of that person, was asked but not answered, or was answered ambiguously.
Analysis
Now, we can begin looking down the columns of the matrix, both within and across roles, to see what is happening. Scanning the first two columns (Salient Characteristics and Size Up) shows us that many teachers—notably in English—see the new remedial program as prescriptive, with little latitude given for adaptation (tactics: counting and making comparisons). And the teachers who see the innovation as prescriptive are also those who have used it the longest, suggesting that prescriptiveness was highest when the program was first introduced (tactic: noting relations between variables). A number of teachers also mention complexity (but note that first-year users are more likely to see the program as simple and easy to use, suggesting program stabilization).
When we drop down to department chairs and central office administrators, the picture is somewhat different. They are more likely to take the “big picture” view, emphasizing the
“curriculum,” “strands,” and the like. Although they too emphasize prescriptiveness (“Depends on being used as it’s set up” or “Works if followed”), they either do not give clear answers on the issue of complexity or (as in the case of the curriculum director, a major advocate of the program) say that
“any teacher can use [it] successfully.” But teachers, faced with an initially demanding, rigid program, are not so sure, it seems (tactic: making comparisons).
Moving to the third column (Anticipated Classroom or Organizational Changes) of Display 7.1, we can see role–perspective differences. Two teachers mention teaming as an anticipated change, one that curtailed their freedom and made them accountable to peers’ schedules and working styles.
Administrators, the field notes showed, considered the teaming necessary to implement the program’s several strands and as a way of helping weaker teachers do better through learning from stronger ones. Even so, they do not consider it a salient change, saying either that no organizational changes are required (“The program is designed to fit the structure”) or that they do not know whether organizational changes were anticipated.
Finally, if we continue the making comparisons tactic, the fourth column (Fit With Previous Style
Finally, if we continue the making comparisons tactic, the fourth column (Fit With Previous Style or Organizational Setting) shows a range of “personal fit” for different teachers, depending on their views of the content, their own styles, and the organizational issues involved. The administrators, however, uniformly emphasize good fit at the organizational level, stressing the appropriateness of the curriculum and its fit into the existing structure; the director also invokes the fact that teachers wrote it.
In short, a matrix of this sort lets us see how perspectives differ according to the role, as well as within a role. In this case, users from the English department who came in at the onset of the program had an initially tougher time than later users or math and science users. A within-role analysis, moving across rows, shows that the superintendent, as might be expected, knows very little about the innovation. More surprisingly, the principal does not either. In this case, a recheck with the field notes (tactic: following up surprises) told the field-worker that the formal role description for high school principals in this district actually forbids them from making curriculum decisions, which are the province of the curriculum director and department chairs.
We also can apply the tactic of making if-then tests. If the director and the chairs have a shared province of work (curriculum decisions), then their views of the innovation should resemble each other more closely than the teachers’ views. Looking vertically once again, we can see that department chairs’ views are much more like those of central office administrators than those of teachers.
The role-ordered matrix display emphasizes different roles as sources of data and perceptions. It is also possible to develop a role-ordered matrix that treats roles as targets of others’ actions or perceptions. (For example, how are teachers treated by department chairs, principals, and central office personnel?)
Clarify the list of roles you consider to be most relevant to the issue at hand; avoid overloading the matrix with roles that are clearly peripheral. Differentiate the matrix by subroles (e.g., teachers of math or science) if relevant. If your case is an individual, role-ordered matrices may well be helpful in showing how role partners view or interact with the person at the center of your case.
Notes
Indicate clearly when data are missing, unclear, or not asked for in the first place. Return to field notes to test emerging conclusions, particularly if the decision rules for data entry involve, as in this case, a good deal of condensation. Role-ordered matrices, because of our prior experience with role differences, can lend themselves to too quick conclusion drawing. Ask for an audit of your analysis from a colleague (see Chapter 11).
Context Chart Description
A context chart is a network, mapping in graphic form the interrelationships among the roles and groups (and, if appropriate, organizations) that make up the contexts of individual actions (see Display 7.2).
Applications
One problem a qualitative researcher faces is how to map the social contexts of individual actions economically and reasonably accurately—without getting overwhelmed with detail. A context chart is one way to accomplish these goals. Context charts work particularly well when your case is an individual—they show you the real richness of a person’s life setting.
Most qualitative researchers believe that a person’s actions have to be understood in their specific contexts and that contexts cannot be ignored or held constant. Contexts can be seen as immediately relevant aspects of the situation (where the person is physically, who else is involved, what the
recent history of the contact is, etc.), as well as the relevant aspects of the social system in which the person appears (a classroom, a school, a department, a company, a family, a hospital ward, or a local community). Focusing solely on individual actions without attending to their contexts runs the risk of misunderstanding the meanings of events. Contexts drive the way we understand those meanings, or, as Mishler (1979) notes, meaning is always within context, and contexts incorporate meaning.
Most people do their daily work in organizations: They have superiors, peers, and subordinates;
their work is defined in a role-specialized way; and they have different relationships with different people in other roles in their social vicinity. But you are not simply drawing a standard organizational chart; you are mapping salient properties of the context. Also, your chart will not be exhaustive or complete. It is a collection of organizational fragments or excerpts. (In Display 7.2, e.g., custodians, secretaries, and the immediate subordinates of most of the school district office personnel are excluded.) Context charts also can be drawn for people in families or in informal groups or communities.
Example
Networks ought to reflect the core characteristics of organizations: authority/hierarchy and division of labor. So it ought to show who has formal authority over whom and what the role names are. But those things don’t tell us very much. We should also know about the quality of the working relationships between people in different roles.
Suppose you were interested, as we were, in organizations called schools and school districts—
and with the general problem of how innovations enter and are implemented in those organizations.
The display should show us who advocated the innovation, who is actually using the innovation, and people’s attitudes toward it (whether or not they are using it). The display should show us how the specific school we are studying is embedded in the larger district organization. Above all, we need a display that will not overload us with information but will give us a clear, relevantly simplified version of the immediate social environment.
Display 7.2 shows how these requirements were met after a field-worker made a first visit to Tindale East, a high school involved in implementing a new reading program. The analyst selected out the roles and groups that are most critical for understanding the context. District office roles are above, school roles below. The network is thus partially ordered by roles and by authority level.
For each individual, we have a name, the age (a feature the analyst thought was important in understanding working relationships and career aspirations), a job title, whether the individual was a user of the innovation or not, and whether his or her attitude toward the innovation was represented through magnitude codes:
+ = positive
± = ambivalent 0 = neutral
Special symbols (such as *) are applied when the individual was an innovation advocate or influenced implementation strongly. The relationships between individuals are also characterized (positive, ambivalent, and neutral). Once past the upper echelons, the display simply counts individuals without giving detail (a secondary context chart at the level of individual teachers was also developed but is not shown here).
To get the data, the analyst consults field notes and available organization charts and documents.
The decision rules look like this:
• For information such as job title, number of persons, and so on, assume accuracy for the moment, and enter it.
• A relationship rating (how X gets along with Y) should not be discounted by the other party to the relationship, though it need not be directly confirmed.
• The “innovation advocate” and “high influence” ratings should be given only if there is at least one confirmation and no disconfirmations.
• If there is ambiguous or unknown information, enter “DK.”
Analysis
After a context chart has been constructed, the researcher reviews the hierarchies, flows, and magnitudes entered, in combination with the field notes, to develop an analytic memo or narrative that tells the relationship story thus far. An analytic excerpt about Display 7.2 reads as follows:
Looking at lines of authority, we can see that only one central office person (Crowden) has direct authority over department chairs as they work on the innovation. Crowden is not only an advocate but also has high influence over implementation, and seems to have a license from the superintendent to do this.
The department chairs, it appears, have three other “masters,” depending on the immediate issue involved (discipline, teacher evaluation, scheduling). Because, in this case, the innovation does involve scheduling problems, it’s of interest that V. Havelock is not only an advocate, but has actually used the innovation and is positive toward it. We might draw the inference that Crowden serves as a general pusher, using central office authority, and V. Havelock aids directly with implementation issues;
the field notes support this.
Note, too, that Principal McCarthy (a) is not accountable to the superintendent for curriculum issues and (b) has a good relationship with V. Havelock. Perhaps McCarthy gets his main information about the innovation from Havelock and thus judges it positively.
So the chart shown in Display 7.2 helps us place the actions of individuals (e.g., Crowden, V.
Havelock) in context to understand their meaning. For example, when Crowden, discussing the innovation, says, “It is not to be violated; its implementation is not based on the whim of a teacher at any moment in class, and its success is not dependent on charismatic teachers,” the chart helps us understand that this prescriptive stance is backed up with direct authority over department chairs for curriculum issues—an authority that is accepted neutrally. In short, the analyst has been employing the tactic of seeing patterns or themes, as well as subsuming particulars into the general (see Chapter 11 for more on these tactics).
The symbols employed for Display 7.2 were Miles and Huberman’s original magnitude codes, but you are not bound to using them. Context charts can employ other visual devices to enhance analysis.
For example, dashed lines can be used to show informal influence, while thick lines suggest strong influence. Font size can be used to represent power relationships—for example, the names in a larger or bolded font have more authority than the names in a smaller font. Circles can be drawn enclosing informal groups and subcultures. Linkages to other affecting organizations in the environment can be added. Physical contexts (e.g., a classroom, the teacher’s desk, resource files, student tables and chairs, and entrances) can be mapped to help understand the ebb and flow of events in a setting. And for an organizational context that seems to change a lot over a short time, revised context charts can be drawn for comparison across time.
Notes
Use context charts early during fieldwork to summarize your first understandings and to locate
questions for next-step data collection. Keep the study’s main research questions in mind, and design the context chart to display the information most relevant to them. If you’re new to qualitative research, keep your first context charts simple. They can be embroidered as you continue the fieldwork.
Describing Variability
A construct table shows the variability or range of a central construct in a study. A conceptually clustered matrix charts participants’ varying perspectives about selected concepts. And a folk taxonomy systematically charts the unique ways in which participants organize and categorize their worlds.
Construct Table Description
A construct table includes data that highlight the variable properties and/or dimensions of one key construct (or concept, variable, category, etc.) of interest from a study (see Display 7.3).
Applications
Construct tables are particularly valuable for qualitative surveys, grounded theory, and phenomenological studies since they enable an analyst to focus on one core item of interest (a construct, concept, variable, core category, phenomenon, etc.). Traditional grounded theory charges the researcher to examine the dimensions or variable ranges of a property, and a construct table assembles that variability for analytic reflection.
Display 7.3
Lifelong Impact: Variability of Influence
Although you may have a general idea in advance about the properties and dimensions of some major variable, such as “lifelong impact,” such variables do not usually become clear until real case