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).