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7 METHODICAL PROCEDURES

In this chapter we present a number of different techniques, which by the methodical procedures (see Figure 1.10) for the different views can be designed as effective methods for creating knowledge. The chapter also takes up issues around validity, reliability and objectivity. Presented here are some techniques that are specific for different methodological views as well, techniques that in several respects characterize these different views and their actions in the study area.

PROCEDURES AS LESSONS IN HARMONY

The description of the different methodological views has, for defensible reasons, not followed a completely uniform line. One methodological view is not like another, which means that we need somewhat different ways of describing them. We would like to add to this treatment a bit before we proceed. The descriptions of the first two views – the analytical view (Chapter 4) and the systems

view (Chapter 5) – were illustrated, among other things, with examples of different theories and results to which they have led. This was less appropriate for the actors view (Chapter 6); there we referred to metatheories, which are not comparable to the theories of the other two views. This is explained by the presumptions or lack of presumptions about reality made by the various views. From this it also follows that the analytical view and the systems view, to a greater extent than the actors view, stress the importance of charting earlier studies and their results within a given field of research/consulting/investigation before the next study is undertaken. This will be fairly obvious if we consider the following. If reality is presumed to be filled

with facts, interest will of necessity be directed toward how this objective and/or subjective factive reality appears, that is, the researcher/consultant/investigator aims at using or developing reproduction theories. If we instead presume, as in the actors view, that reality is basically a social construction dependent upon us as observers/actors, interest will be directed toward the way this reality is constructed, that is, the researcher/consultant/investigator aims at developing construction theories. But the actors view, as we know, also “reproduces” a social reality by using its descriptive and ideal- typified languages. These constructions are called metatheories because they not only include these languages (their own construction), but are also the prerequisites of their development. This could be perceived as the actors view going one step further than the other two views

(it brings an understanding of, or depicts, both the construction of reality and its appearance).

Arbnor, I., & Bjerke, B. (2008). Methodology for creating business knowledge. ProQuest Ebook Central <a onclick=window.open('http://ebookcentral.proquest.com','_blank') href='http://ebookcentral.proquest.com' target='_blank' style='cursor: pointer;'>http://ebookcentral.proquest.com</a> Created from indwes on 2021-04-06 17:28:32.

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But this opinion is wrong insofar as the other two views’ conceptions of reality and science do not presume a construction process – reality as such is a given. In this sense we cannot say that one view goes further than another. At the same time we should point out that the proponents of the actors view claim that they

can go further (or rather deeper) by presuming reality to be a social construction. What they are saying is that it is not until one realizes that reality is and will remain a social construction that many of the unsolved problems of business (and of society in general) can be studied. It is pointless for us to argue for or against this opinion here. What we can say, however, is that the different conceptions of reality that are associated with our views lead to different ways of doing research/consulting/investigation and to differently created worlds of knowledge, in both practice and theory; whether any view can go further or deeper than another view can only be decided by reflecting on the different conceptions of reality. The question thus becomes: can you go further – can you explain and understand more – by changing (changing yourself) to another view’s conception of reality, instead of staying with the one being used? This leads to something we have already pointed out: “You can never establish empirically which view is the best one.” Because we are attempting, as far as possible, to present each of the views on its own terms,

it becomes necessary to let the descriptions of the different views vary. The reason we have devoted so much time to ultimate presumptions is because we hope through this book on methodology to create conditions for independent and critical thinking in the reader. The reality that creators of knowledge face when conducting a study is not exactly the reality described in textbooks. Modifications must therefore always be made to textbook presentations. These modifications cannot be made without first having gained an insight into the ultimate presumptions on which a view is based. Otherwise it would be like opening and changing a car’s gearbox without understanding the “presumptions” on which it is based, namely, its relations to the engine, the road, and the use of the car generally. We mentioned earlier that methodology’s task is to clarify how different methodological

views and study areas harmonize in terms of problem formulations, research/consulting/investigation plans, methods and techniques. Because it is not possible to define this “harmonology” in advance in an “instrumental” way, methodology will to a great extent be about developing the insight and understanding that make it possible for creators of knowledge to develop some degree of “harmonology” on their own. The presentation so far has aimed at producing independent and critical thinking about what

the three methodological views try to achieve and under what circumstances they should be used. These are necessary prerequisites for developing an operative paradigm. An operative paradigm cannot be developed just from technique centered knowledge and associated skills; also necessary are a deep insight into, and feeling for, that which is being studied and for how the “tools/processes” the creator of knowledge uses for orientation are related to ultimate presumptions (the foundation of any methodological view). This is because the purpose of an operative paradigm is to create a fit between ultimate presumptions about a methodological view and the nature of the study area (see Figure 7.1).

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Figure 7.1 Operative Paradigms Create Fit

OPERATIVE PARADIGMS

In the introductory chapter of this book, we described how scientific theory uses the paradigm concept to describe the relation between ultimate presumptions and concrete methodological views. In the same way, we proposed our idea of being able to describe the relation between a methodological view and an area under study by using the operative paradigm concept. Through this concept, which is determined in terms of methodical procedure and methodics, we have acquired a means of communication that will allow us to compare various studies, reports, essays, and the like. If this can function as a bridge of language commonality among the proponents of various methodological views, we have come very far on the way to both a better understanding and a better communication within the area of methodology, which continues to be characterized by a high degree of conceptual confusion. This becomes especially important with the intensification of knowledge in production, service, marketing, and other areas in business. To invest resources strategically in developing knowledge without making it clear in

advance what the knowledge is knowledge about – that is, what ultimate presumptions it is based on – would not be cost effective (more about this kind of “knowledge audit” in the final chapter). Therefore, we can expect an increasing interest in the questions that methodology addresses. In our earlier descriptions of the operative paradigm concept we stressed its character of

aspiring to fitness, in other words, that it might function as a general instrument for testing relations between a chosen methodological view and the actual study area. From this it follows naturally that the development, as well as the form, of the operative paradigm will be different for each of the three methodological approaches (in the text from now on we use both the concepts of view and approach, alternating depending on whether we are referring to the view as such or to its use in practical application – the use of either one concept or the other is, however, not something which the reader needs to attach any greater importance to than has already been stated). If we were to describe the development of an operative paradigm in each of the approaches

in terms of their degree of formalism and instrumentalism, we would find that the analytical approach ranks highest, the actors approach ranks lowest and the systems approach is somewhere in between. This, of course, would also characterize when in a study the operative paradigm is ready as well as its final form. Because of its greater degree of formalism and instrumentalism, the analytical view considers the development of an operative paradigm as

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less problematic. The analytical approach, as we know, operates with a greater number of a priori starting points than the other approaches, which leads to its operative paradigm being ready relatively early in a study. This also indicates that the operative paradigm in an actors approach study will not be complete until the study is complete: an actors approach operative paradigm is developed gradually over the course of a study. The time for developing the operative paradigm in the systems approach varies between these two points, depending on the circumstances of a given study. What happens in the development of an operative paradigm can, as mentioned before, be

divided up and described in terms of methodical procedures and methodics. We remind the reader of our definitions: Methodical Procedure: the way in which researchers (or any other creators of knowledge) arrange, develop, and/or modify any technique, theory, or previous result in a methodological approach, or, alternatively, develop a new technique.

Methodics: the way in which researchers (or any other creators of knowledge) relate and arrange the techniques-become-methods in their study plans, and the way in which a study is actually approached.

Researchers/consultants/investigators, just like other people, have access to a number of means in their work. These means vary. There are physical means like paper and pen, microscope, computer, and the like; what we might call instruments or tools. Among the tools used by creators of knowledge we can also count the special terminology available for the purpose of creating knowledge. In business we have a set of such terms, such as costs and revenues, budget, manager, brand, segmentation. By a technique we mean the way in which a subactivity of creating knowledge is carried

out. The tools just mentioned (and others) will be useful in this context. When a sample is taken (a technique), a random numbers table (a tool) can be used. When a personal interview is carried out (a technique), a digital recorder (a tool) can be used. Furthermore, the interview must be conducted in a terminology (a further tool) that the respondent can understand. One could also say that available techniques are the alternative actions open to the creators

of knowledge. Part of their work may also be to develop new techniques, increasing the number of alternative actions available. The interesting question is, of course: When should the researcher/consultant/investigator

carry out, for instance, a face-to-face interview, where should it take place and how should it be arranged? If we also keep in mind why a technique is used, we have four questions with which we can assess techniques. In other words, if for each technique we ask:

When? Where? How? Why?

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a specific technique should be used, we arrive at the level of methods. We maintain that a technique in itself is worthless. A technique has no value until it becomes a method. To turn a technique into a method or to develop a new technique into a method is what we call a methodical procedure (please note: adapting and possibly modifying previous results and theories is also referred to as methodical procedures). This implies a serious answer to the four questions above. Whether a new technique is to be developed, or which technique is to be chosen and how it

might be modified, are determined by:

the methodological view chosen the character of the study area.

It is to some extent possible to examine in principle what a technique should look like in relation to a particular methodological view. But it is not until it is related to the study area that a technique takes on its definite shape, that is, becomes a method. In other words, the methodological view and the character of the study area (e.g. which

problem and/or opportunity seems to be at hand) will determine the rules for choosing, arranging and developing techniques into methods, that is, the alternative actions to create knowledge. The connections between techniques and methodological approaches – in other words, the

development of methodical procedures – are the subject of this chapter. From methodical procedures we take a further step when we come to methodics. We then

come to the study plan as a whole, and to the actual conduction of the study. This will be illustrated in Chapter 9. There are major differences among methodological approaches as far as methodical

procedures are concerned, but the differences are even greater for methodics. Methodical procedures and methodics go hand in hand. In practice they cannot be fully separated. Every methodical procedure pays attention to its background, the methodics of which it is,

or will be, a part. Any methodics would be empty if it did not contain seriously prepared methodical procedures. Nevertheless, in this chapter we will treat only methodical procedures and how they can be related to various methodological approaches. We do this in order to initiate the reader gradually into understanding the relations among the methodological view, the operative paradigm, methodical procedures and methodics – in other words, the development of an operative paradigm. We believe that an exchange between “theory” (this chapter) and “practice” (Chapter 8,

“Methods in Language and Action”) is useful for continued learning. After reading Chapters 9 to 12, where we deal with methodics vis-à-vis our methodological approaches (in Chapter 9 in theory, in Chapters 10, 11 and 12 in practice), we are confident that the reader will have a practical and consistent methodological orientation. We begin by reviewing what are considered to be “common” groups of techniques:

1. selection techniques (for units of study)

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2. traditional data collection techniques 3. measurement and reliability techniques 4. validation techniques.

Even if our three methodological approaches often regard/make use of these groups of techniques differently (sometimes even define them differently), we believe they constitute something of a common ground for every effort to create knowledge. We are aware that several groups of techniques are thus excluded, for instance: a. techniques for making definitions b. techniques for relating to previous knowledge c. mathematical and logical techniques d. application techniques.

We covered techniques for making definitions in the illustrations of the basic concepts of the three methodological views presented in Chapters 4, 5 and 6. Techniques for relating to previous knowledge were brought up at the ends of these same chapters. Mathematical and logical techniques belong primarily to the analytical view (see brief discussion in Chapter 4), and will be considered later in this chapter when we treat techniques specific to the various methodological approaches (e.g. sampling). The differences in application techniques for each of the views should be clear after reading the examples. After treating some “common” techniques, we will further clarify the differences among our

methodological views. This will be done within the framework of one approach at a time, by specifically describing:

For the analytical approach:

sampling validation techniques

For the systems approach:

historical studies case studies

For the actors approach:

dialogue language development

We treat these techniques separately even though they could be used in more than one methodological approach (but with modification, and often after redefinition). For instance,

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validation techniques are presented in the group of “common” techniques as well as under “specific” techniques. This chapter ends with a reflection of how our three methodological views position

themselves in relation to the problem of objectivity.

SOME “COMMON” GROUPS OF TECHNIQUES

Techniques for selecting units of study

In this section we provide certain general principles for using techniques to select units to be studied when creating knowledge. We will not go into deep mathematical or statistical aspects (they belong mainly to the analytical approach, which we will come back to). Our goal here is only to present a sufficient basis for understanding the different methodological views’ relation to such techniques. Every study (no matter which view it uses) wants to reach certain results, even if they are

only preliminary. Reality (no matter how it is defined) can never be encompassed in its entirety. In every effort to create knowledge we can attempt to study, explain, and/or understand only a part of it. This part we can define as “a piece of history” (i.e. a temporal limitation) or “a piece of the existing state” (i.e. a spatial limitation). No matter how we do it, our area of interest becomes limited, that is, we must select only what seems relevant for the study. In the analytical view reality is seen as a great number of independent units, which means

that statistical sampling theory can be a decisive means for achieving the ambitions of the view (we will return to this theory in further detail). Representativity (i.e. how selected units represent the larger totality that is to be described or explained) becomes crucial for whether or not the research ambition will be generalizable. Finding the average and the pattern around this average is what every analytically based person trying to create knowledge aims for. If this is the case, it means that when the description or the explanation of the selected units is present, the description and the explanation of the area of interest as a whole is also present. The principle of independent units of study is not accepted by the systems view. A systems-

based person trying to create knowledge perceives his or her reality as consisting of systems, which by definition means dependent relations on the one hand, and sometimes partly unique cases on the other. The concept of representativity, in a strictly statistical sense, is therefore not valid for the systems view in general. It is therefore common to work with case studies here (more on these later). Another reason for working with case studies in the systems approach is simply that from a practical point of departure, analyses of complex objects require extensive effort. The cases studied by the systems creator of knowledge cannot be selected on the principle that they will represent all other systems (in the sense of being constructed the same, or of behaving the same way). Nevertheless, in the meaning given them by the systems view, they can represent a certain type of system (if the intention is to study a system type). So, the real systems selected for study within the systems approach usually

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follow other principles:

They are versatile and can therefore bring comprehensive light to phenomena being studied. They are interesting in the sense of leading the development in some direction. This could mean that we will look for unique, or at least divergent, cases.

The concept of representativity is rarely used in the systems approach. Because the actors view is primarily interested in specifying the meaning and the

construction of social phenomena, starting from its inherent egological sphere, the talk about representativity is of less interest here too, and can even be seen as invalid. According to the actors view, representativity makes no sense in a socially constructed reality because it represents only shallow clichés of statistically generalized situational “tones of meaning” (see the subheading “Denotation of conceptual meaning and scientific language” in Chapter 6). The concept of representativity is therefore extremely rare in the actors approach. It is customary, however, to apply principles similar to those used for selecting cases in the systems approach when selecting individual companies in the actors approach. When selecting individual actors within those companies or elsewhere, some of the following principles, alone or in combination, are usually applied:

recommended selection understanding selection problem/opportunity-oriented selection.

A recommended selection means letting different actors recommend other interesting actors. By an understanding selection we mean a selection of actors who, in the diagnostic development of understanding, turn out to be important in some way. A problem/opportunity- oriented selection means choosing individuals who are in some way connected to the problem/opportunity being studied. These people may not have been seen as important in the diagnostic development of understanding, but in order to get a versatile description of the significance of the problem/opportunity and possibly raise the level of understanding, certain actors are nevertheless chosen. This might in turn raise the level of understanding with which new selections will be made, but now as understanding selections. In other words, there is often an extensive interchange between these three types of selection.

Traditional techniques for collecting data

There are two main categories of traditional techniques for collecting data.

using material previously collected, so-called secondary information collecting new data, so-called primary information.

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Primary information can be collected in three ways:

direct observations interviews experiments.

Secondary information

When using secondary information, the creator of knowledge often faces two problems:

1. Compatibility. Previously collected or secondary information might have been collected for another purpose, from another perspective, and so on. Existing data may therefore be classified differently or start from a different measurement scale and/or from other definitions. Consequently, these data might not be compatible with those the researcher/consultant/investigator wants.

2. Trustworthiness. Researchers/consultants/investigators can be unsure about the extent to which previously collected data are correct.

Primary information: Direct observation

You are observing when you conduct a face-to-face interview. Studies of secondary information, including viewing all types of recording or listening to recordings, are also a kind of observation. Both of these cases are what we might call indirect observation (and/or listening). Direct observation, on the other hand, consists of a situation of creating knowledge that, as a whole, is arranged around observing what happens in the present. Four types of direct observation can be differentiated, as shown in Figure 7.2.

Figure 7.2 Types of Direct Observation

A situation with “complete observation” is difficult to achieve. It is technically complicated to arrange a situation in which you can observe without those being observed knowing it. It is

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also morally questionable whether a researcher/consultant/investigator should observe people without their knowledge and consent. Another technical problem, of course, is that you can directly observe only what is happening here and now (including directly observing something taking place “there”, if you have a camera pointed at the place). So a researcher/consultant/investigator must know when and where to observe.

Primary information: Interviews

A very common traditional technique for collecting primary information in business is through interviews. The following types can be differentiated:

personal interview (face-to-face) telephone interview mail questionnaire group questionnaire (a questionnaire constructed by the interviewer and administered to an entire group at the same time and place).

Some important concepts for this traditional technique for collecting data are:

standardization: the same questions for everyone nonstructured interview: interview with a low degree of standardization open questions: questions without fixed alternative answers closed questions: questions with fixed alternative answers interviewer effect: the respondent is influenced by the interviewer panel effect: the panel (a group of individuals who are repeatedly interviewed) usually develops to a point where it consists of “specialists” who are no longer representative of the social group, consumer type, and so on, from which they were originally selected.

Primary information: Experiments

The traditional technique for collecting data referred to as experiments is aimed directly at reproducing causal relations and therefore regarded as a technique for collecting data only in the analytical approach. However, this does not prevent the other methodological approaches from using the term “experiment”, but as the other two views consider causal relations as irrelevant descriptions of social relations, the term will have a very different meaning in these other two views, and even a different meaning in between the two. Successful experiments in the analytical approach starts with creators of knowledge finding

(or arranging) two identical situations. Then they deliberately interfere with one of the situations so they can study the effects of this interference. After the interference has established itself, they measure the difference(s) between the two situations. The effect of the deliberate interference is the difference in the measured results between the experimental

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group (interfered with) and the control group (not interfered with). The interference is the cause of these effects (see Figure 7.3). We call this an experiment with a control group and with post-test measurement only.

Figure 7.3 Experimental and Control Groups in an Experiment

There are a number of variations in how experiments are arranged. Researchers/consultants/investigators can measure both the experimental and the control group before the experiment takes place in order to check for differences that may exist between the groups even before the experiment. These differences will have to be considered later when the effects of the interference are evaluated. Another variation when working with the experimental group only (i.e., omitting the control group) is to measure the experimental group’s characteristics both before and after interference. There are yet other experimental variations. A complete traditional experiment in the analytical approach should make two kinds of

operations possible:

1. Manipulation: manipulation of the independent variable 2. Control: elimination of any influence from background or intervening variables, either by

eliminating the variables or by isolating their influence. This means, among other things, that the researcher/consultant/investigator is clear about the experimental context and that it is possible to repeat the experiment, preferably in an identical context.

Conducting experiments in a “natural context” is called field experimentation. The possibilities for manipulation and (above all) control are less in field experiments.

The approaches’ relation to the traditional techniques

The analytical approach and traditional techniques

The analytical view is based on the assumption that all creation of knowledge should be cumulative (larger and larger slices of factive reality will be mapped as one proceeds). This approach therefore uses secondary information extensively. When presenting the results of a study, the analytical approach consequently attaches great importance to disclosing the way data were collected, how samples were taken, what definitions were made, what measurement

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scales were used, and so on. The analytical approach also tries to collect all sorts of primary information and then uses

all three of the above-mentioned methods of collecting data. One can therefore say, without exaggeration, that the traditional techniques for collecting data to a large extent are related to this approach. Within this approach it is also usual to standardize the interview questions in order to be

better able to compare the different answers. The analytical researcher/consultant/investigator aims (if possible) at closed questions. This will simplify the compilation of the results (the so- called coding). The analytical view points out, however, that it is difficult to conduct strict experiments in practice in business, no matter how desirable they may be.

The systems approach and traditional techniques

The systems approach does not conduct experiments as they are defined above, because experiments as they are done the analytical way are based on conditions that are not valid for systems. The systems approach uses secondary information and primary information from direct observations and interviews, however. Even so, experiments in a “looser”, trial-and- error sense are, in fact, often undertaken in the systems approach. As we have seen, a correctly conducted experiment in the analytical approach requires that two essentially identical situations can be found or created. Furthermore, analytical approach experiments attempt to establish a causal relation whereby the independent variable (which is deliberately interfered with) explains the dependent variable, all other things remaining equal (“the experimental philosophy”). The systems view questions both the possibility of finding two such similar situations and being able to discuss matters in terms of causal relations and of “all other things remaining equal”. Secondary Information. Because the systems view’s conception of reality claims that it has

to deal with a more complicated reality than the analytical view, and that real systems are often relatively different from each other, secondary information concerning the environment of the real system being studied, and, above all, concerning other real systems, is used with great care. However, secondary information within the real system being studied (minutes, statistics, documents, etc.), material that may very well reflect both the environment and other real systems, is used extensively (this source of information is also common in the two other approaches). Direct Observation. This is used almost to the same extent as in the analytical approach.

The conditions permitting direct observations and the interest in doing so, however, are not as common. (Among other things, the systems view is very interested in explaining and understanding the history of real systems – which by definition is not directly observable. We will come back to studying the history of systems.) On the other hand, direct observation is frequently combined with interviews. Interviews. Interviews are used extensively in the systems approach, usually in the form of

personal interviews. Rarely, if ever, are broadly elaborated questionnaires administered.

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The actors approach and traditional techniques

Virtually all methods of collecting data used in the actors approach, where the egological spheres are to be apprehended, start with the dialogical situation. For the creator of knowledge collecting data for use in the actors approach, a dialogue is an engagement in a situation on equal terms with other participants. You talk, listen, notice, question, observe and, on the whole, act as you do in everyday life – but with a disciplined reflective attitude (we will return to the actors approach and the dialogue in further detail). In this context, what separates creators of knowledge from other actors is the way in which the creators of knowledge interpret, notice and arrange data. The engagement varies, of course, with the degree of information the researchers/consultants/investigators are trying to obtain, what understanding they are aiming at, and what actions they intend to conduct. Actors must never feel that researchers/consultants/investigators seem belittling, self-righteous, supercilious, critical or triumphant when feeding back an interpretation. This would strongly bias their ability to receive any potential insight. Because this insight is not the researchers’/consultants’/investigators’ private “invention”; it is also the actors’. It was developed through their cooperation in constructing a fresh social reality. It follows from this that only personal “interviews” as dialogues, and what we have referred

to as indirect observation (and participative observation – see experiments below), should be used when reproducing the egological sphere. Historical material is collected through various kinds of documentary analyses and the time

frame that selected actors cover. We will not take up how to do a documentary analysis now; the reader can find some information in the discussions of applications using the actors view (see Chapters 8 and 12). We want to stress again what we said at the end of Chapter 6 about using historical descriptions in the actors approach. It is through such descriptions that the approach aims, among other things, at creating meaningful “mythical images” – the “truth” of which can be proven by the actions they trigger. Depending on the study area, there may be certain “hard” factors that can be of interest for

reflecting denoted conceptual meaning in another perspective. These include any that answer questions in terms of:

how many? how often? is it associated with something special? what colours? what age, sex, and so on? what income? and more.

When charting these, researchers/consultants/investigators can, in principle, use all of the techniques for collecting data described above under “Traditional techniques for collecting data”. But keep this in mind: a denotation of conceptual meaning as used in the actors view can never be structured in a questionnaire or be studied in terms of, for instance, “how often?”

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Denotation of conceptual meaning can only be interpreted and understood, not explained or quantified (see Figure 6.1). Sometimes in the actors approach we refer to data obtained from “hard” factors as “actual/factual data” to stress that “factual” data, according to this approach, are given their actuality by the actors involved, and it is not permanent. Experiments in the sense used in the analytical approach do not exist in the actors approach.

The actors approach does, however, use “experiments” (emancipatory interactive action) in the sense of creative experimental activities (as creative and direct action – see Chapter 6 under “Action”) together with actors out in the field, in an attempt to receive information, discover the potential in what is factual, and develop descriptive languages. These experiments of a creative character can contain anything from pedagogic dramas presented on film to direct business activities.

Measurement techniques and techniques for controlling reliability

In principle, there are four measurement scales:

1. Nominal scale. Nominal scales only allow the creator of knowledge to place measurements in groups – such as man/woman, foreman/worker, or inside/outside the factory – but not to indicate any order among those groups. Two measurements can therefore only be equal or not equal to each other on this scale.

2. Ordinal scale. Ordinal scales include the possibilities of nominal scales and also allow ranking among the measurements, such as larger or smaller (or possibly equal). Many attitudinal scales are of this type.

3. Interval scale. Measurements are further specified on interval scales. They make it possible to tell the distance between the measurements. Because an interval scale does not have a natural zero point, the whole scale can be moved (allowing scale transformations) without making it less useful. One example is the Celsius scale. Its zero point is arbitrary, and the scale can be easily transformed into a Fahrenheit scale. Many exam-grading scales are of the interval type.

4. Quota scale. Quota scales are the most “precise” of the four types. Their zero point is fixed, and all possible mathematical operations can be applied. Examples include height, weight and length, as well as profit, market share and salary. Interval scales and quota scales are both called cardinal scales.

In the analytical approach, the terms sensitivity, precision and reliability are used for characterizing scales. Sensitivity is increased when a scale is refined, such as when it measures dollars singly instead of by the thousands. Precision can be increased only by shifting to a new scale (downwards in the categorization above), going from an ordinal to an interval scale, for instance. The scale with the highest precision is the quota scale. A scale is reliable if it gives the same results under repeated use. Similarly, a measurement is reliable if the same result is obtained with repeated measuring. The reliability of, for instance, a test of a person’s suitability for a certain position or task can be controlled in several ways. One way is

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to conduct the same test more than once; this is called test-retest. Another way is to conduct two similar, parallel tests at about the same time. A third method is called split half, which means that a test is divided into two halves, each containing similar questions, and so on. If a whole group is tested, two similar tests can be allocated randomly in the group to check the tests’ reliabilities against each other. The analytical approach (which is often very quantitatively oriented) aims at increasing

sensitivity as well as precision. It also recommends controlling reliability as often as possible. The systems approach is less quantitatively oriented than the analytical approach. Its

measurements are therefore not as precise (as defined above). Such precision is also not considered worth aiming for. As in so many other contexts, the systems approach takes a pragmatic position (see Appendix). The important thing is what a measurement can be used for, not the way a measurement was made or its precision. The concept of reliability is rarely used. Considering what has already been said in this chapter about the actors approach in the

contexts of techniques for selecting study units and collecting data, we remind the reader that denotation of conceptual meaning as an expression of the logic of ambiguity and social movement cannot be quantified, which means that scales, as they are defined above, and control of reliability are not used. This is a natural consequence of the ultimate presumptions on which the actors view is based. What is commonly referred to as a “lack of reliability” in social science results is, according to the actors view, not a deficiency but rather proof that the ultimate presumptions of the actors view are relevant. A social life that is presumed to be in a state of constant dialectic flux with a subjective status cannot be studied in a traditional reliable way. In order for that to be possible, according to the actors view, an ultimate conception of reality as an objective possibility, with a summative and causal character – that is, in accordance with the analytical view – would be required. When it comes to other “hard” factual factors, factors that can be treated quantitatively, the

actors approach uses scales just like the analytical approach does. It is very rare, however, for these to be used in actors-oriented studies.

Validation techniques

Because validation techniques are rather different for the different approaches, we discuss them under each individual approach.

The most important factor for assessing the quality of different measurements in the analytical approach is their validity. This concept can be seen in two ways: (a) concerning a test or a measuring instrument one can ask: “What is measured by this test (or measuring instrument)?”; and (b) concerning the measurement itself one can ask: “Does this result reproduce factive reality: that is, is it true?” Unless a relatively adequate answer to each of these questions can be given, all measurements will be useless, according to the analytical approach.

They may not only be useless but even become harmful. This is easy to see when considering Arbnor, I., & Bjerke, B. (2008). Methodology for creating business knowledge. ProQuest Ebook Central <a onclick=window.open('http://ebookcentral.proquest.com','_blank') href='http://ebookcentral.proquest.com' target='_blank' style='cursor: pointer;'>http://ebookcentral.proquest.com</a> Created from indwes on 2021-04-06 17:28:32.

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the following: A company is about to enter a new market with an existing product and is using a sales forecast based on a number of different measurements as a guide. If these measurements do not measure what they are supposed to measure but instead measure something like the demand for a supplementary product, or if they are wrong (even if measurements are about future demand for the product in question), the results will not only be useless, they may be frankly “disastrous”.

Validity in the analytical approach can therefore first be said to be the extent to which the indicators of a measuring instrument correspond to a definition. This means that validity affects the core of the relation between theory and data. Validity can therefore be improved by a continuous adjustment between our methods for constructing theories and for conducting research/consulting/investigation. This again emphasizes the importance of using methodical procedures to choose and develop the right techniques for the particular methodological view and study area. It is pointless to develop or to choose techniques, or both, in a theoretical or empirical vacuum. After using a measuring instrument correctly (according to its instructions), checking its

validity becomes a measurement of the extent to which the results are correct or true. The closer to reality we come, given a certain definition and goal, the higher the instrument’s validity. Because it is so important, even decisive, in the analytical approach to “hit” reality, we

discuss specific validating measurements for the analytical approach later in this chapter (see “Some ‘specific’ groups of techniques” below). At this point we will only mention that, in general, measurement reliability can be controlled directly by simply doubling or repeating the measurement. The validity of the measurements themselves, on the other hand, can be controlled only indirectly. The only direct way to know whether measurements are true is to compare them to the truth – but if we know the truth, there is no reason to measure it! Furthermore, as far as the analytical approach is concerned, validity requires reliability.

The opposite, however, is not necessarily the case (see Figure 7.4).

Figure 7.4 Validity and Reliability

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Suppose a company, according to Figure 7.4., wants to extend its customer base – reach more consumers – by investing in environmental sustainability. To be sure, they conduct two consecutive tests to find out what potential customers think of their new investment. So, the company is interested in reaching those who know of the company today and their investment for the environment, but who do not at the moment have any business with them. In order to conduct the tests students at a nearby Business school are engaged. The students divide themselves into three groups which each independently set up different methodical procedures, including sampling, construction of questionnaires and formulating questions for personal interviews, and respectively establish their methodics for the tests. They present the results, where the stars in pairs in Figure 7.4 illustrate the two conducted tests of each the three groups in the study area. As can be seen in the figure, the three groups are not equally good as creators of knowledge. We can also say that the results from Group C are not biased. Validity can therefore also be defined as absence of systematic bias. A decisive test in the analytical approach of whether measurements are correct, that is,

valid, is if they can be used to make good forecasts.

The systems approach regards the validity problem somewhat differently. Because of the lower degree of generality and absoluteness of systems theory, the connections among theory, definitions and reality are not as strong as they are in the analytical case. The requirement is not so much that definitions must correspond with existing theory or be operational, as that they are perceived to be important and relevant to the creator of knowledge as well as to other participants from the real system engaged in the process of creating knowledge. In other words, these people have an interest in and an opportunity to decide whether a measurement is correctly made and whether the results are reasonable and correct. Sometimes outside “experts” are also asked to make a judgement of the measuring procedure and its results. A common systems approach procedure for guaranteeing, to the extent possible, that

measurements are correct is to reflect the real system from as many angles as possible. To do this, creators of knowledge take every opportunity throughout the course of a study to be in the real system as long and as often as possible, to talk to as many people as possible, and to study as much secondary information as they can. A decisive validity control in the systems approach lies in the effects that can be achieved

by applying the measurements.

The concept of validity as used in the actors approach has a number of different meanings that range from how researchers/consultants/investigators use dialogues to discover whether or not their interpretations are correct, to the “credibility” and “sincerity” of a knowledge report. The reason there are no concrete validation criteria in the actors approach is due in part to a

socially constructed reality being so interactive (in dialectic flux) that the suitability for traditional validation is limited. Many actors researchers/consultants/investigators have said repeatedly that the only real

validation is the extent to which the actors accept the results and interpretations made. This, however, is a qualified truth. A common sign that an interpretation is “correct” is that the actor reacts emotionally and denies it. If the interpretation had not been “correct” and therefore had

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not influenced the actor emotionally, he or she would not have had to react emotionally – by denying it – but could instead have presented a well-prepared opinion of the interpretation. In a similar fashion, actors may accept incorrect interpretations that they themselves experience as positive. Apart from this type of validity check, the necessity of having a pragmatic attitude toward

validation of results presented by the actors approach is often mentioned. This means that practical usefulness decides the value of the results (compare with similar opinions in the systems approach). This type of validation is questionable, but it can occasionally be used and should not be rejected. A further way of talking about validation is the extent to which “dialectic tension” can be

created for a continuing dialogue, that is, whether the results can enhance the dialogue and initiate actions in an understanding, emancipating and innovative perspective. To clarify somewhat the situation just described, we present a few ideas that can be of help

in guiding validation in the actors approach. First, we make a distinction between validating the process and validating the results. Second, we are of the opinion that validation can take place as either a scientific or a practical validation. A practical validation of the process takes place through the feedback mechanisms

normally present in social contexts among people (the creator of knowledge is not thrown out by the actors; instead the actors show a continued or increasing interest). A practical validation of the result can be called the combination of the pragmatic attitude and the one to create dialectic tension for a continuing dialogue and emancipatory interactive actions. The scientific validation of the process could be established if

researchers/consultants/investigators show clearly in their reports the basis on which the different interpretive patterns are developed, that is, the logic and the reasonableness in the development of these patterns. Furthermore, the subjective interpretation must be clear, that is, scientific concepts must be clearly shown to be rooted in the first hand expressions of the actors in the study area. This leads to a further requirement: that the concepts are to some extent translatable into everyday language. The scientific validation of the result has to do with the relation of the result to existing knowledge, that is, whether the result might be useful in developing the scientific branch (business) as such. This brings a certain kind of intersubjective testability to the scientific result. The reason we

say “a certain kind” is that the result cannot possibly be tested in all aspects. This testability must usually be limited to an interpretation of reasonableness by the scientific community. In the sense of the actors approach, a good practical validity is a necessary prerequisite for

a good scientific validity. A good scientific validity, on the other hand, is not a necessary prerequisite for good practical validity.

SOME “SPECIFIC” GROUPS OF TECHNIQUES

The analytical approach and sampling

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Most people understand intuitively what a sample is. The basic idea is to select a smaller number of units out of a totality (called a population in this context) in order to arrive at a description of the totality from this smaller number. The decisive test of a sample, then, is the extent to which it is representative of the population about which the creator of knowledge wants to draw certain conclusions. In measuring terms, we might say that a good sample must have validity. Validity, as we know, means that there are no systematic biases. Therefore, a sample has

validity if overestimations and underestimations of individual elements in the sample balance each other. We know that no sample completely represents a population in all aspects. But if there is a variation, it must be random, not systematic. This random variation is usually called standard error, and it is measured by the sample variance (or corresponding standard deviation). The lower this is, the better, all other things being equal. The ambitions and assumptions on which the analytical view is based fit sampling theories

well. Theories for sampling (and its associated statistical applications) are extensive and quantitative. We know that the analytical approach is happy to use mathematical tools. In order for statistical sampling theories to be used as effectively as possible – for what is called the law of large numbers to be valid – it is necessary to be able to select study units from a population, units that are assumed to be independent of each other. We know that the analytical view is based on precisely this assumption. A brief description of some of the most common sampling methods includes:

1. Random sample

simple random sample systematic sample stratified sample multistage sample

2. Subjective sample

quota sample judgement sample

A simple random sample requires that creators of knowledge have some kind of list of the units that belong to the population. Then they allow probability, and probability alone (e.g. a die, random tables or computer-generated numbers), to decide which units are to be in the sample. A more practical variation, and one that is often used, is to select systematically from a list every tenth unit, for example, or the unit at the top of every left-hand page. The creator of knowledge must check the list to be sure that it is not constructed so that the sample contains too many of just one or a few kinds (e.g. systematically selecting all persons whose family name starts with Q, expecting these to be representative of the population at large, is probably not recommended). A stratified sample results from dividing the population into groups, so-called strata, from

which subsamples are taken. These groups should be as different from each other as possible. For sampling done this way it can be statistically proven that, with the same sample size as for

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other techniques, an average better representativity (i.e. lower sample variance) will result, or alternatively that one can achieve a certain average representativity with a smaller sample. Simple random, systematic and stratified sampling require a list of the whole population to

start with. This is not the case with a multistage sample, which as the name implies is obtained in several steps. For instance, if the researcher/consultant/investigator divides the population into geographic areas and the first step is to be a selection among these areas, only lists of the units that live in the selected areas are needed. In the second step, any of the other sampling techniques can be applied to these areas. For practical and economic reasons, the creator of knowledge often takes samples through

subjective procedures. Quota sampling involves taking a sample that, according to predetermined background variables, has the same characteristics as the population. A judgement sample is made up of units that are subjectively judged to be representative. As far as representativity (the decisive question for sampling theory as well as for the

analytical approach in general) is concerned, we point out two circumstances that are often misunderstood: A. The representativity of a sample is determined not by how large a proportion of the population is selected, but by the total number of units contained in the sample. In other words, a correctly selected sample of 200 units out of a population of 10,000 units has, in principle, a lower standard error (sample variance) than a sample consisting of 100 units taken from a population of only 1,000 units.

B. It is not possible to determine a priori (in advance) whether a random sample will be more representative than a subjective sample. In random samples, however, the standard error can be calculated. This cannot be done in a subjective sample.

The analytical approach and validation of measurements

The analytical approach wants to chart and measure factive reality. To determine whether this is in fact happening as the research/consulting/investigation proceeds, in other words to validate measurements, is considered to be essential. Considering the way in which measurements are validated, we can talk about three kinds of

validity; they should be combined whenever possible:

1. face validity: acceptance 2. internal validity (logical or theoretical validity): relevance 3. external validity (empirical validity): consequence.

Face validity is a subjective assessment of the plausibility of the results and can be done by the creator of knowledge. It is also possible to ask concerned respondents or external experts whether or not they accept the results.

Internal validity (also called relevance) is primarily concerned with the logical relationship Arbnor, I., & Bjerke, B. (2008). Methodology for creating business knowledge. ProQuest Ebook Central <a onclick=window.open('http://ebookcentral.proquest.com','_blank') href='http://ebookcentral.proquest.com' target='_blank' style='cursor: pointer;'>http://ebookcentral.proquest.com</a> Created from indwes on 2021-04-06 17:28:32.

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between a study and existing theory in the area. The hypotheses of the study (derived through deduction) should be formulated in such a way that they in fact shed light on the theory the study is based on. When several dimensions of a theory are measured at the same time, the results of those dimensions should be compatible with each other. If, for instance, a study is made of the motivation and the efficiency of a specific factory cell, theory gives us reason to expect that the most motivated people will also be the most efficient ones.

External validity is related to the possibility of generalizing results beyond the actual study area. External validity exists if results can be used in other events or characteristics that are contemporary with, but not of main interest to, the study (i.e. criterion validity), or as a basis for making a forecast of future consequences (i.e. predictive validity). If a person claims to be very interested in, and at ease with, modern planning techniques, but time shows, perhaps in word and deed, incompetence in this area, we might question the validity of that person’s statement. If, on the other hand, we take a sample of political opinions that later proves to fit the actual election results well, the validity of the measurement in question is high. Crucial for external validity, in other words, is the relation (fit) between our measurements and the actual manifestation of other, external (contemporary or future) correlated indicators.

The systems approach and historical studies

The systems approach looks at its real systems as “living” wholes. Such systems often exist long before they are studied and so can be seen at least partly as products of their own history. It is therefore often essential to explain and understand the background of a real system’s historical time in order to explain and understand what it is today – and thereby also its ability to face its future. Being interested in describing the history of a real system, in other words, is not egotistical.

History is of interest only to the extent that its footprints still exist (cf. Lindqvist, 1978). Reproducing history and collecting historical “facts” is never simple – it is not like

collecting coins or stamps that can be arranged in attractive patterns for public viewing. It is always, to some extent, a question of interpretation, either directly through various “relics” such as documents or other manifestations or evidence still in existence, or indirectly through someone else’s interpretation – people who can relate the experience of the past at first or second hand. There are consequently two ways to gain a knowledge of history:

1. various documents (secondary information) or other types of evidence (e.g. a prototype of a company’s first product)

2. interviews with those who have experienced (or heard of) the past.

Without going into detail, let us take a brief look at the specific problems connected with reproducing the history of a real system. More specifically, let us assume that we want to reproduce the history of a company. Let us also assume that we as creators of knowledge have

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access to existing data, be they from public sources or from sources internal to the system (for instance, various kinds of documents and other evidence produced in the course of history), or from contacts with various persons inside or outside the system. Reproducing the history of a real system through access to only external material or interviews does not lead to specific methodological complications, though it does make the interpretive work more difficult (something that should not be taken lightly). First, let us look at secondary information, which is always selective. History is never

documented (or manifested) in its entirety. The materials, furthermore, can be of highly differing quality and character. Secondary information also always carries a message, sometimes one that is quite biased (because there is always a purpose behind documentation). Finally, the material may tend to have a personal or else an institutional character. Personal material can include correspondence, letters to the press and articles written for a newspaper. Institutional material might include reports, minutes, annual reports, various types of statistics, and more. Similar points of departure are also valid for studying and analysing other (physical)

manifestations of history that exist today, like buildings and other constructions, machines, products and trademarks, and so on. One important difference between documents and other historical manifestations, however, is that the latter may not contain words, pictures, and the like. The study and analysis of these, then, should be combined with other techniques for collecting information about history. A creator of knowledge has reason to be selective about historical material (and

manifestations). The material must first be assessed for its usefulness. Second, a creator of knowledge must try to trace the origin of the material (which is not always obvious). Third is the interpretive procedure itself (in the mind of the creator of knowledge). These three aspects are related and interdependent. Usefulness depends partly on the questions the creator of knowledge works with, partly on

the trustworthiness of the material. Trustworthiness can, in turn, sometimes be verified by other documents and the like – but it is often a matter of finding the originator. For example, there is probably a different degree of trustworthiness behind a public annual report or the minutes of a meeting, compared with a letter from the personnel manager to the general manager concerning rumours about a pending strike in one of the company’s factories (a strike that may never have materialized). Further aspects of determining origin, apart from the person or persons behind the material, can involve determining whether material is genuine or forged, attempting to date it, and deciding whether it is a first hand source or otherwise. Much can be said about the interpretation itself, but space does not permit further elaboration. Let us only say that it is important to understand historical material from its own contemporary perspective, which often requires extensive studies of the spirit of the times in the environment of the system being studied. Another way of gaining knowledge about the not too distant past is, as already mentioned, to

ask people who experienced (or heard about) this bit of history to tell their story. This also has special problems. One is that people forget. Another is that they may deliberately lie (maybe to present themselves in a more favorable light). But even if they really try to remember and do tell the truth, the researcher/consultant/investigator must be aware that such stories are always

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fragmented, open to reinterpretation (unless they are about specific facts), and often a matter of rationalizations. So, reproducing history is not an easy task for creators of business knowledge. They must be

detectives and be persistent and broad-minded, as well as open and honest. And don’t forget that creativity is a prerequisite for critical thinking and reflection (see Chapter 2).

The systems approach and case studies

The real systems that the creator of systems knowledge tries to describe, explain and understand are often complex both to grasp and to reproduce. One problem is the historical description, which we have just touched upon. But there are other problems that are specifically related to the systems researcher/consultant/investigator’s method of working with one or a few cases as the area of investigation: that is, case studies. Among other things, we can imagine two very different situations. One is coming to the real

system as an academician, the other is being invited as a consultant (or other type of invited investigator). Access to the real system, the expectations of its members and what they can and will tell rest on very different conditions in each of these situations.

Table 7.1 Expectations

Academicians will Consultants will • be matter-of-fact and objective • be matter-of-fact but subjective • be many-sided and impartial • be one-sided and partial • be theoretical • be practical • have plenty of time • have a time limit • want to describe, explain and understand • want to change • be inexperienced and difficult to understand • be experienced and professional

Table 7.1 lists differences in the expectations that are commonly held by members of the real system about academicians and about consultants. There are many exceptions, of course, but the patterns described in Table 7.1 shed light on some common differences in the two instances. Further differences between academicians and consultants are listed below.

1. Although neither academician nor consultant will escape the political game that takes place in all real systems, it is a natural part of a consultant’s work. This is because consultants normally aim at changing things (for the better) and will thereby disturb existing power balances in the real system. Consultants can therefore expect very different behaviour from those who believe they will gain from change compared with those who fear it. But even academicians will come across expressions of power play and should avoid becoming involved. Both alertness and openness are required to avoid becoming a part of this often complicated and subtle play.

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2. Consultants are usually required to be confidential. Academicians, on the other hand, want to use their systems knowledge to gain merit, that is, they want to publish their findings and results. It is not uncommon for managers in real systems to oppose publication of certain information (usually financial results and sales figures, but also plans and personal information). Sometimes academicians can avoid compromising the scientific value of their publication by disguising the presentation, or by making the real system anonymous (and probably telling the reader that such anonymization has taken place).

3. Experienced consultants usually have a rough plan and model ready after being given their mission. Academicians, though they may want to test a specific model, are often considerably more flexible. Their first goal might be to classify the type of system before proceeding with a more complete description, which may be labourious as well as extensive.

4. Consultants’ results are judged by the client in terms of profit, return, new perspectives, or some similar success factor. Academicians’ “judges” might include the members of the real system (e.g. for comprehensiveness, impartiality and plausibility), but are more likely to be the scientific community, including the academicians’ supervisors and peers who will use more academic criteria.

It is not uncommon today in systems research to place real systems cases in metaphors. Metaphors make it possible to look at real systems as something else and therefore raises questions which would not have been asked in explanatory pictures of reality. Using metaphors is also a methodical procedure. Using metaphors in order to understand systems and some of the consequences of doing so are treated in Chapter 5 (“Examples of classic systems interpretation”).

The actors approach and dialogue

Dialogue was illustrated earlier in Chapter 6, and examples will be given in the more applied parts of this book. But because this section presents techniques specific to each of our three methodological approaches, the dialogue has a place here, too. Dialogue is different from discussion as well as debate by having completely different

intrinsic purposes. This can also be read from the language origins of the different concepts. We bring these differences up in order to deepen the understanding of the central role of the dialogue as an investigative and innovative instrument in the actors approach. As mentioned earlier, dialogue comes from Latin dia, which means through and logos

which means words. The purpose of the dialogue is to clarify differences in order to later transgress them toward something new, where differences are conveyed but, as it were, dissolved (synthesized) in a deepened understanding and meaning of life, that is, the parties of the dialogues are looking for a highest common denominator (compare discuss below). In the dialogue, consequently, agreement is to come about through what is different. One so-called typical win/win situation. Discuss comes from dis which means apart and cutere which means cut (dash to pieces).

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The purpose of the discussion is similar to the analytical approach to divide – to cut apart – where the parties of the discussion are looking for the lowest common denominators to start from when summarizing. Here, instead, agreement is to come about through what is similar (compare dialogue above). Debate comes from battere, which means battle. The purpose of the debate is to beat your

opponent with arguments and tricks of rhetoric. Here we get one winner and one loser, and there is no question of coming to an agreement through any specific intrinsic principle. From this we can understand that the opinion of the actors view is to look at dialogue as the

most important technique for “looking for truth” and groundbreaking acts. It is important to understand that dialogue in the sense of the actors approach is not only about agreeing on a kind of friendly intimacy but also about forging the very master key in the construction of new social reality. So, a dialogue in the sense of the actors approach is distinctly different from an interview

(see Table 7.2).

Table 7.2 Dialogues contra interviews

Below we give a brief summary of some related aspects of dialogue:

Participating honestly in a dialogue is a difficult art; succeeding is the sign of a skilful creator of actors knowledge. One must also be honest with oneself as a creator of knowledge in these contexts. The point is to enter the dialogue “without knowing” (in spite of the fact that we always know a lot and have many prejudices, see Chapter 2), and to leave the dialogue feeling that one has in fact grown in capacity and has dared to give something up, not simply had something confirmed. A creator of knowledge must be inside and outside the dialogue at the same time. A researcher/consultant/investigator is simultaneously an actor and an observer with ambitions to produce knowledge. Participating in a dialogue does not mean using only spoken and written language. As in

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all social contexts, body language must also be considered. Social reality is continuously constructed and confirmed. A dialogue is therefore not a phenomenon that is strictly limited in time. The researcher/consultant/investigator must also be aware of what preceded as well as of what will follow the dialogue. Participating in a dialogue as a creator of knowledge can be compared with being a creative and curious artist. An artist “puts pressure” on the present in order to find alternative interpretations, possibilities and openings. Artists are also not only able to shape that which they see, but also to decide which perspective and what aspects of it are to be considered.

Dialogue is essential for the creation of understanding and meaningful actions within the framework of a world in which knowledge is created with an interactive development of understanding as one of its guiding principles. Kamprad, Ikea’s founder says: There are too many desks in Sweden and too many people sit at them too much of the time. The obvious risk is that a person loses his contact with reality and with the people he is to serve […] I would like to make my closest colleagues do what I do, to be out there among people, trying to listen to their everyday problems, learning to understand their thoughts and wishes. You have to live in reality, not isolate yourself from it. (1993: 6; authors’ translation)

According to the actors view, this is valid whether it concerns knowledge-creating activities or other activities in business – and elsewhere.

The actors approach and language development

There are many metaphors we can apply to language – reflected image, cultural manifestation, means of communication, guide, entry (or exit) – but no matter how we look at it, language is what makes us uniquely human. Many creatures can communicate, many creatures use “signals”, but only human beings can see language as symbols, even talk about language. This uniquely human aspect is the basis of the actors view’s interest in language. What we have words for, we can perceive. It is even likely that if you work in an

organization and talk in terms of planning, systems and control, you see planning and lack of planning everywhere, feel that you are part of various systems, and have a feeling of being controlled. If, on the other hand, the environment communicates in terms of service, creativity and solidarity, you probably feel (and act) differently. This can also be expressed in dialectic terms: we use language as a tool in order to create

and sustain reality and to communicate these processes (externalization), yet at the same time language can be said to use us as its tool in order to communicate, create and sustain reality (internalization). Existing language is, at every moment, not only an encyclopedia of all we can see, but also an encyclopedia of all we cannot see. When we think like this we are also able to understand how people are phenomena of language-dependency and also how they reflect upon

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this dependency of language too seldom. The same way we use language subconsciously, we can also use it consciously to create

new thoughts, open up new perspectives, create involvement, etc. It is possible, according to the actors view, to describe a thing almost totally without feelings, but it is also possible to make associations and enlighten the imagination. One may start to think critically and connect thought with feeling. The way in which we work with language and its different varieties of expression is related to those knowledge-creating interests and knowledge ambitions (Figure 6.2) that drive the creator of knowledge to use language in ways that bring understanding about. As creators of actors knowledge we try to develop procreative concepts which shape and

vivify the world for us, but also provide old concepts with new energy and innovative direction, give concepts poetic timbre and depth. It must therefore be of interest to understand one’s own and (above all, as a creator of actors knowledge) other actors’ finite provinces of meaning in terms of language, and to understand that it is possible to create new finite provinces of meaning and consequently to renew oneself. The creator of actors knowledge can consciously change the finite provinces of meaning held by others, or can at least free others from locked-in frames of reference, giving them new creative power by developing their language. All kinds of social science language development must, according to the actors view, be

based on a relation that focuses on meaning and which relates the actors’ first hand expressions with the scientific concepts in order for a developing tension to arise in the interface between the different worlds. If a creator of knowledge is building his/her language development only on other relations, for instance, previous theories and established clichés in his/her own field, this is, according to the actors view, to be compared with trying to describe summer using the language of winter. “Procreative words” we call those concepts in language development that have the capacity

to catch the creator of knowledge creating him/herself as well as the knowledge creativity. These are concepts that are “loaded” by the right kind of energy for the study area and become decisive in the process that makes the conscious language come alive. Let us remind the reader of what we mean by “the creator of knowledge creating him/herself”. In Chapter 6 we wrote like this: “The actors oriented creator of knowledge is therefore, in different ways searching for the inner quality of those micro-cosmoses he/she is meeting. And also, at the same time, he/she tries to re-create this quality in him/herself in order to be able to understand and to transfer these experiences through ‘the emancipatory interactive action’.” Based on experience we know that this process of transferring these experiences through,

among other things, descriptive languages and emancipatory interactive actions (see Table 3.1) is subtle at the same time as it is very concrete. New words creating culture are introduced in the study area through concrete action! It is through the use of the concepts in concrete situations that the meaning and the relevance are developed. It is a kind of work, which requires feeling and insight about how the procreative words arise themselves as carriers of meaning for the creator of knowledge in the interface between the actors’ first hand expressions and the scientific perspectives.

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Knowledge creating interface of language development

Nothing can exist or create meaning without its opposite. Light would not be light without darkness, life gets its meaning through the presence of death, change can only be experienced as a background of permanence. An operative and rational language needs a personal and emotional language as its opposite. Different provinces of meaning are each other’s productive opposites. We live and work in a field of tension between a number of opposites and it is in the nodes

of these opposites, in their interface, that what is interesting and challenging exists. Sea and land meet and create the beach – constantly the same, but always different. Day meets night and delivers dawn, and night meets day in twilight. The day does not destroy the darkness of night and night does not take the light of day – they are instead each other’s conditions for keeping the rhythm alive. And so is also the meeting between creators of knowledge and actors – where the dialogue is creating an interface of unexpected possibilities. It is an interface that in itself contains something more, a power that can broaden and refine our finite provinces of meaning. It is possible to train oneself (and other actors) to use language more creatively. We can

present six principles, in our actors approach, for how to make language understood and developable. They all aim at starting the critical reflective thought and broaden the perspective with the creator of knowledge when he/she develops language in order to give substance to his/her experiences. The language principles below can also be used, of course, in interaction with the actors in the study area.

1. Language cleaning. This removes “masking words”, reveals established illusions, renders power expressions empty, and more. A few examples can illustrate the principle:

In the old days we talked about unemployment when we referred to unemployed people. Now we can hear terms like redundant, dehired or terminated. Why? Why do we say that we produce care when we take care of each other? Why is war referred to as fighting for peace? Why do we say collecting data when data are constructed? Why do football coaches refer to their players as material and cogs in a team machinery?

By cleaning the language, the creator of knowledge can see the hidden grammar of the concepts that shape our thoughts.

2. Language reduction. When we talk about reduction here, we mean the search by the creator of knowledge for the words that are most common in the vocabulary of his/her research (pre-scientific concepts are also included), and the actors’ everyday vocabulary, in order to discover what is happening in dialogues and descriptions when these words are reduced in numbers – that is to say, when the creator of knowledge and the actors are forced to look for other words in their expressions of meaning other than those commonly used and taken for granted.

3. Language polarization. This sets one concept against its “opposite”, puts invisible signs up against visible ones and makes a potentially creative interface become visible:

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reflection proflection resume prosume manufacture autofacture insight outsight react proact official onicial

4. Language shift. This is the understanding of a terminology in terms of a specialized language, such as financial language, hacker language, caring language, sports language, arts language, music language, adventure language or budget language. This means that the creator of knowledge consciously tries to describe phenomena using words and perspectives borrowed from a language field other than the one in which the phenomena are linguistically rooted.

5. Language subjectification. This makes language come alive, includes feelings and subjects, increases ambiguity and richness of aspects, and reduces mechanical pictures (metaphors) and the reification of human beings; in short, it includes the full living subject in bureaucratic, business-oriented and scientific languages of description.

6. Language poetring. Here the point is to give rhythm and provide metaphors to the describing and procreative language in order to bring it to a kind of poetic level which creates nearness and exactness between experience and transfer of meaning (see “The procreative report” below). Metaphors become here one of the most important forms of substantiating for linguistic/semantic innovation which we, in the name of the actors view, have access to in order to describe and clarify “discoveries” and ideas.

The procreative report

In the same way as an artist or a poet tries to endow substance with that context, those feelings and those experiences he/she is carrying, the actors oriented creator of knowledge tries to transfer his/her experiences. This is often about writing a report of some kind. Here the creator of knowledge is usually introducing the different “empirical” sections of

the report by summarizing his/her experiences in procreating reflections. These introductory reflections (“mini art works”) are done in a metaphoric and critical language, sometimes on the verge of surrealistic, in order to deepen and contextualize the human significances – the meaning structures – which then in these “empirical” sections “are allowed to talk” their own language by referring to the first hand expressions of the actors. To add the “poetic” dimension here (see language principle number 6 above) is, according to the actors view, also a way to become more exact in the knowledge-creating transfer of experiences. To give the procreating reflection as many dimensions as possible not only makes the description more rounded but also more precise in the direct meeting with the reader. Because if you neglect the reader’s need for meaning being created in the – “poetic” – context of transferring experience, the reader will subconsciously add these dimensions, which might completely disfigure what the creator of knowledge wants to say.

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For the reader of a procreative report it then becomes possible in the borderland between the procreating reflections of the creator of knowledge and the actors’ own linguistic description to either experience that “Yes, it is probably so”, “This is also a way to think”, or argue against and reject. In here it is useful, according to the actors approach, to go beyond the explaining, that which is said to be more generally valid but which, according to this view, stands as a symbol for what is superficial – what may not concern anybody but still is said to be valid for most. The actors creator of knowledge wants instead to provide a reading which is both intellectual and exciting, where the reader can actively participate, thanks to the openness of the text through that dialectics which develops between three different exactnesses: (1) the reader; (2) the procreating reflections of the creator of knowledge; and (3) the first hand expressions by the actors. The exactness of the creator of knowledge can also be found in those models (see Figure 6.11) that are ending the report. This final exactness is then set up against the reader’s freedom to deliver the potential in the factual. The core of a procreative report is consequently a willingness from the side of the creator of knowledge to excite the knowledge- creating dialogue at all levels, no matter which way it develops. The expression format of the report, where the creator of knowledge, with creative and

scientific precision, is trying to “paint” the picture of complex phenomena using a procreative language and the different language models of the actors view (see Figure 6.12), we could call artistics – an interpretive pictorial language creating meaning. It is a knowledge-creating expression format that is totally different in kind from statistics as a descriptive language (see Figure 6.1).

THE PROBLEM OF OBJECTIVITY

An overview

The topic of objectivity is extensive and touches on several difficult problems in the philosophies of science, ethics and epistemology. In 1916 one could, for instance, in The Philosophical Review read the following by Jones: “In classic British or German philosophy, probably no question has been so variously treated, or so differently ranked, as the problem of objectivity” (1916: 778). The issue of objectivity concerns the very conception of science and knowledge in society and the role of creation of knowledge here. Let us raise some questions that can indicate the wide range of ramifications of the subject:

Is such a knowledge possible that can provide universal and trans-cultural explanations, applicable to all people in the world no matter when? Or are explanations culture, gender and time specific and therefore impossible to apply generally? Is such a knowledge possible that can reflect back reality without distortion? Or is knowledge one part of reality itself, such that it can never reflect its own truth? Does what we call “truth” exist in the field of social sciences? Does the development of the social sciences mean that knowledge is constantly added to

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such that insight and understanding continuously create a higher quality of human life? Or does this increase in knowledge take place mostly as an accumulation of information in the scientific society with little importance in a general human sense? Has the accumulation of knowledge in social research made us wiser, smarter and more insightful than our ancestors?

All these questions touch upon the problem of objectivity one way or another and are not, as we can see, easy to answer. They also reflect our three methodological views and their ultimate presumptions; so part of the answers could be found in this book. This section is therefore only a small overview on the topic; it should be seen as an

unpretentious attempt to clarify the problem in order to raise somewhat our level of awareness of a complicated issue. People have long debated, both verbally and in writing, whether the social sciences can reach objectivity and, if they can, whether it would be worth the effort. One participant in this debate a long time ago was the Nobel Prize winner in Economics, Gunner Myrdal, and it is starting from his work that we write this little résumé. In Objectivity in Social Research (Myrdal, 1969), he raises a number of questions that are still representative of the issues involved: The most fundamental methodological problems facing the social scientist are, therefore, what is objectivity, and how can the student attain objectivity.… How can a biased perspective be avoided? More specifically, how can students of social problems liberate themselves from (1) the powerful heritage of earlier writings in his field of inquiry, ordinarily containing normative and teleological notions inherited from past generations and founded upon the metaphysical moral philosophies of natural law and utilitarianism from which all our social and economic theories have branched off; (2) the influences of the entire cultural, social, economic, and political milieu of the society where he lives, works, and earns his living and his status; and (3) influences stemming from his own personality, as moulded not only by traditions and environment but also by his individual history, constitution, and inclinations? (1969: 3–4)

The presentation of objectivity actually concerns two separate levels, the macro and the micro. We can say that the macro level stands for the value judgements and normative theses that are part of the discipline as such, whereas the micro level centres on the individual researcher/consultant/investigator. It is primarily the micro level that will be taken up here. Myrdal also seems interested in objectivity mainly at the micro level when he asks repeatedly how individual social scientists will be able to reach any objectivity in their profession, and whether there is a method by which they can ensure the highest possible objectivity in their research. Myrdal recommends that science brings its values into the open, making them conscious, specific and explicit, and openly clarifies how they determine theoretical constructions: “I am arguing here that value premises should be made explicit so that research can aspire to be ‘objective’ – in the only sense this term can have in the social sciences” (1969: 56). These value premises must furthermore fulfil a number of demands:

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They must be explicitly stated and not concealed as implied assumptions. They must be as specific and concrete as the valuation of reality requires. They must be purposefully selected as they are not, a priori, self-evident or generally valid on the grounds of being founded only on facts or on the “nature of things”. (1969: 63)

The numerous ideas that exist in the scientific tradition and the social environment that creators of knowledge belong to, influence, to various extents, their research/consulting/investigations. The fact that the lack of awareness of this is rarely critically discussed led Myrdal to state: It is astonishing that this taboo is commonly respected, leaving the social scientist in naiveté about what he is doing. To destroy this naiveté should be the object of the sociology of science and scientists, the least developed branch of social science. This is important, as these influences, if they are not controlled, are apt to cause systematic biases in research and thus lead to faulty knowledge. (1969: 4–5)

Myrdal continues by formulating a number of requirements that may protect us from biases:

1. We clarify the values that actually determine our theoretical and practical research/consulting/investigation.

2. We scrutinize those values from the point of departure of relevance, significance and feasibility in the society under study.

3. We transform them into specific value premises for the research/consultation/investigation.

4. We determine approach and define concepts in terms of a set of value premises that have been explicitly stated (see Myrdal, 1969: 63–7).

The problems that exist when clarifying value judgements are, among other things, related to scientists’ fear of explicitly stating evaluations that exist at the micro level. Scientists therefore often try to hide their evaluations by expressing them as conclusions drawn from facts. But making one’s value judgements conscious and expressing them explicitly is not a simple matter. Such a procedure will surely lead to new problems of rationalizations and dubious after- constructions. The first step in improving on this “low level of awareness” might be a sort of inter-

reflection among creators of knowledge. They might talk about how values in knowledge creating activities can be interpreted in terms of reasonableness and how they might be legitimized. As Myrdal points out, it is difficult to claim that one’s scientific activities and results are value-free: They are always and with logical necessity based on moral and political valuations. … The fact that political conditioning plays such a decisive role in the choice of field for research should make us more aware and apprehensive of that other type of conditioning:

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namely, of the approaches we choose in research, by which I mean the concepts, models, and theories we use, and the way in which we select and arrange our observations and present the results of our research. That second type of conditioning, though not necessarily the first one, is what leads to biases. (1969: 48–9)

Furthermore, we can be in relative agreement that values also play an important role in choosing and delimiting problems. It seems reasonable to assume this, because behind every such choice there must be certain ideas about what is important to study. We can conclude this brief overview by saying that the only thing that seems reasonable in

this context is both a higher degree of self-awareness on the part of researchers/consultants/investigators, and that researchers/consultants/investigators have an “external” awareness of the political power systems that implicitly influence their creations of knowledge.

The analytical approach and the objectivity problem

The analytical approach aims at being as objective as possible and claims that this problem, in practical terms, is not as insoluble as is sometimes claimed. It is not possible to be totally value-free when, for instance, choosing problems and selecting methods. But researchers/consultants/investigators should try to make implicit (hidden) values explicit. In their reports creators of knowledge should declare their own values, and how these might have influenced the results. It is then up to the reader to judge the consequences. In the analytical approach, creators of knowledge should try to use methods that leave as

little room as possible for personal values. Even then, however, they should be explicit about their own values. Talking about the differences between objectivity at the micro and macro levels, the

analytical view believes that science as such (macro level) can be objective. The scientific tradition (critical attitudes, free and open debate, tolerance for deviant behaviour) is the best guarantee that values have as little impact as possible. Many analytical scientists refer to intersubjectivity rather than objectivity. Intersubjectivity

means that there is conformity among the research results reached by different individuals in their studies, given the same circumstances and competence, and applying the same methods. Intersubjectivity can exist without value agreement. Aiming for reliability and validity can be seen as the analytical approach’s means of achieving intersubjectivity.

The systems approach and the objectivity problem

There are only differences in degree (not in kind) between the attitudes of the analytical approach and the systems approach to the objectivity problem in general. In principle, a systems creator of knowledge agrees with what has been said under “The analytical approach and the objectivity problem” above (however, compare the differences between the two approaches’ attitudes to the problems of the concepts of reliability and validity). Even when it

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comes to the problem of objectivity, the systems approach shows its pragmatic attitude. Once again, the results of applied studies are seen as more important than, in this case, the objectivity in descriptive studies or studies that determine relations.

The actors approach and the objectivity problem

Starting from the actors view conception of reality, and in particular the concept of intentionality, requirements for objectivity stand out as being absurd and illogical. Humans are subjective beings – they create reality out of their own subjective intentions, and they create the objects in the environment from their subjective intentions and then locate them through their senses. How, then, can it be possible for creators of knowledge to study subjectivity objectively? They are, after all, objectively a part of the subjectivity. The answer must be that this cannot be done. Not even psychologists studying the behaviour of mice can free themselves of values, because they already have opinions about mice as mice. Intentionality says that we first, through our egological sphere, create a mental image (a

value judgement) and then, through our senses, look for a situation in the environment that corresponds to the image. The final image (the finite province of meaning) is created in the dialectics between our inner images and situations in the environment. Value judgements are prerequisites of our mental experiences. Taking this as a starting point, we conclude that objectivity as normally perceived in contexts of the other two views cannot exist. According to the actors approach, the idea of objectivity is based on an “incorrect” ultimate presumption about how social reality is constructed. Ultimate presumptions that require objectivity probably have their historical origins in problems associated with attempts made by the social sciences to legitimize themselves at their inception a century ago. In order to make studies of subjective beings (man/woman, the creative actor) legitimate, social scientists at that time uncritically adopted the objectivity requirements of the highly regarded traditional natural sciences. The social science interpretation is subjective and should, according to the actors view, be

based on reflection of meaningful data in near and genuine meetings, where the dialogue is the foundation for relevance. “The criterion” for its quality is not objectivity in the sense of the other two views but something meaningful and qualitative to reflect on, something that helps others to keep on creating relevant social reality. Furthermore, the more “vividly” expressive the procreative report is made (see “The procreative report” above), the higher the degree of precision that will be achieved in the overall scientific results. The actors view claims that the more quantified something is, the less precision the numbers are able to cover and transfer (see Figure 6.1). This thought goes right against the concept of the analytical view in particular. The quantitative form of descriptions does not consider the conscious and subconscious “poetic” need of meaning in communication from the receiver’s side but is leaving it adrift. The ostensible objectivity of the numbers does, according to the actors view, permit the creation of the meaning of the numbers by the receiver to flutter completely freely. Taking as its premise that no human beings can free themselves from their biographic

situation and that they can only try to hide basic personal values, the actors approach

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advocates a higher awareness and an open dialogue about the importance of values and their legitimacy in different situations. This is especially true of the micro level, that is, of researchers/consultants/investigators’ more personal values. The more interpersonal level – the macro level – contains paradigmatic starting points, that is, normative and stipulative theses for conducting research/consulting/investigations. Here, too, the actors approach advocates a higher awareness of the starting points based in philosophy and scientific theory on which the methodological approaches are based. As far as extra-scientific normative and stipulative factors, like power and party politics, are concerned, the actors approach advocates an open and critical dialogue in order to prevent these factors from leading to biases in knowledge creation under the guise that value-neutrality is the same as subordinating oneself to the factors that establish power and party politics. Figure 7.5 uses a number of key concepts in an attempt to illustrate the outlook on, and

requirements for, “objectivity” in the actors approach (please read objectivity here as honesty, ethics and high moral standards) in the research/consulting/investigation process and its results. The key concepts are taken from the discussion above, from our discussion of validity, and from Chapter 6.

Figure 7.5 Actors Apporach Requirements for Objectivity

The design process of operative paradigms can be seen as a skill of harmony: how the ultimate presumptions of a view are “playing in concert” with a study area and where the task of the operative paradigm is to make this knowledge developing “concert” sound harmonic. The harmony is a kind of guarantor that those results that are produced are keeping a high knowledge-creating quality. The tools/processes of the operative paradigm for this harmony are methodical procedures, which are discussed in this chapter, and methodics that is brought up in Chapter 9. In this chapter a number of techniques, some which the three views have in common and some which are more specific to individual views, have been brought up and related to the opinion of the different views, respectively,

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as “knowledge creating methods”. The different opinions of the views on concepts like validity, reliability and objectivity are clarified by going to the origin of the concepts and matching them with the ultimate presumptions of the views. In this chapter the reader is shown in detail and in depth how the techniques, by being related to a view, become methods for developing knowledge. The process is consequently called “methodical procedures”.

POINTS OF REFLECTION

1. By the expression “a lesson in harmony” the authors want to describe what? 2. What is it that makes an operative paradigm look so different in the three

methodological views? 3. In this chapter the term approach and view are used interchangably! Why using both

these concepts? 4. What leads a technique to be called a method? 5. There are common techniques that the different approaches use in varying degrees.

The main reason for this variation is, of course, that the different views start from different ultimate presumptions but give some other reasons for these variations!. (The other reasons are, of course, related to the main reason, but we are after those reasons that follow on from that.)

6. If somebody says that a gun when being tested with six shots at a target has high reliability and low validity, then how have the six shots been positioned?

7. How do you want to describe the concepts of validity and reliability? 8. The clarification you gave of the two concepts above – from which view did you take

up your description? 9. In this chapter six techniques specific to the views are mentioned – which ones? 10. Give some important characterics of the six! 11. Objectivity is a concept that has haunted science for centuries. Give some reasons for

why this has been so! 12. Clarify for yourself how the different views look at the problem of objectivity!