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A Professor’s Moral Thinking at the Abstract Level Versus The Professor’s Moral Thinking in the Real Life Situation (Consistency Problem)

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Abstract

We conducted an on-line survey to investigate the professor’s idea of “morality” and then to compare their moral thinking at the abstract level with their moral thinking in the real life situations by sampling 257 professors from the University of Novi Sad. We constructed questionnaire based on related theoretical ethical concepts. Our results show (after we performed exploratory factor analysis) that the professor’s idea of “morality” consists of the three moral thinking patterns which are simultaneously activated during the process of their abstract moral thinking. We have identified these patterns in the following manner: deontological, formal and subjective pattern. In addition, our results show that of the three, the subjective pattern is more activated than the other two during their process of the moral thinking at the abstract level. We also discovered that there is a statistically significant difference between professor’s moral thinking patterns activation level at the abstract level and their moral thinking patterns activation level in the real life situation.

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Notes

  1. Moral thinking takes place at two levels. At the lower, or intuitive, level we simply applied principles that we have learnt, without questioning them. At this level descriptivism (the view that moral judgments are purely descriptive) can seem plausible, and so can intuitionism, which is one of its main versions. We do, at this level, have moral convictions which we cannot easily doubt. However, these convictions support rather simple general principles, which can conflict in awkward cases. For this reason, and because we need to be sure that the convictions are the right ones to have (many people are completely convinced of the most deplorable moral principles), a higher level of thinking is required, to justify them and decide conflicts between them.

  2. The aim of science is theory. Facts or data are meaningless in themselves. They must be linked through propositions which confer meaning. Were we unable to perceive such relationships, our capacity to manipulate, process, or understand facts would be overwhelmed. Relationships recurring with high probability become scientific laws that may be incorporated into a theory covering the domain in which they are applicable. A scientific theory consists of two components: analytic and empirical. The analytic component is the linking of symbolic statements through chains of reasoning that obey logical or mathematical rules but that have little or no operational-empirical content. The symbols involved may refer to line, atom, dimension, force, power (mechanical or social), group, or ideology. Statements involving these symbols may be associated through verbal reasoning, symbolic logic, or mathematics. Whatever the symbols or mode of reasoning, this analytic component of theories can be the creation of the scientist's imagination, the distillation of a scholar's experience with the subject matter, or a tediously built structure slowly erected on a foundation of numerous experiments, investigation, and findings. The empirical component of theories is operational. It fastens the abstract analytic part of a theory to the facts. While the analytic part need have no empirical interpretation, the empirical component must verifiably link to data for a theory to apply to “reality.” Confusion between the empirical and analytic parts of a theory may have militated against a more theoretical use of factor analysis. The geometric or algebraic nature of the factor model can structure the analytic framework of theory. The factors themselves can be postulated. From them, operational deductions with empirical content can be derived and tested. The factor model represents a mathematical formalism departing from the calculus functions of classical physics. The analytic part of the factor model is akin to that of quantum theory. Vectors and their position, linear operators, and the dimensions (factors) of a system are the focus of concern.

  3. Abstract thinking is a level of thinking about things that is removed from the facts of the “here and now”, and from specific examples of the things or concepts being thought about. Abstract thinkers are able to reflect on events and ideas, and on attributes and relationships separate from the objects that have those attributes or share those relationships. Thus, for example, a concrete thinker can think about this particular dog; a more abstract thinker can think about dogs in general. A concrete thinker can think about this dog on this rug; a more abstract thinker can think about spatial relations, like “on”. In general, abstract thinkers are able to perceive analogies and relationships that others may not see and thereby understand higher levels of abstraction. The term abstraction also applies to uses of language. Abstract language is said to include terms that refer to entities other than physical objects and events, for example, “justice” and “freedom” as opposed to terms that refer to actual physical things, like “chair” and “car”. Abstract language also includes indirect uses of language, such as metaphors and figures of speech. For example, a concrete thinker would interpret “People who live in glass houses should not throw stones” to refer literally to breakable panes of glass. An abstract thinker, in contrast, would understand that the figure of speech means that people who have faults of their own should not criticize others. One should be careful, however, not to equate metaphor with abstract. The terms concrete and abstract are also used to suggest how practical or impractical an idea might be. In this sense, concrete ideas are those that have relevance to action (e.g., a recipe is concrete because it states how to cook a dinner; a differential equation is abstract because it is not tied to action in this way). To some extent, concrete and abstract is domain specific For example, for a mathematician, concepts like exponent and equation are second nature and relatively concrete in their meaning. However, that same mathematician might find concepts like value as used in political economy to be quite abstract. The reverse might be true for a political economist. Familiarity with the content in a given domain or specialty area dictates to some extent what will be considered concrete (and therefore easy to understand) and what will be considered abstract (and therefore hard to understand). The ability to think concretely and abstractly is also associated with the ability to transfer what is learned from one context to another.

  4. Moral behavior over time is, in the light of Bandura’s sociocognitive theory, defined by the activation or de-activation of the mechanism of moral self-control.

  5. The University of Novi Sad is now the second largest among six state universities in Serbia. The main University Campus, covering an area of 259,807 m², provides the University of Novi Sad with a unique and beautiful setting in the region and the city of Novi Sad. Having invested considerable efforts in intensifying international cooperation and participating in the process of university reforms in Europe, the University of Novi Sad has come to be recognized as a reform-oriented university in the region and on the map of universities in Europe. Teaching at the University and at  the faculties is entrusted to professors  and teaching associates who hold academic titles prescribed by law (43259 students at undergraduate studies, 2692 attained doctoral degrees, 2897 teaching staff which includes professors, teaching associates, lecturers and 1137 non-teaching staff).

  6. Why we performed exploratory factor analysis on obtained data? Exploratory factor analysis (EFA) seeks to uncover the underlying structure of a relatively large set of variables (in our case items about moral orientations). The researcher's à priori assumption is that any indicator may be associated with any factor. This is the most common form of factor analysis. There is no prior theory and one uses factor loadings to intuit the factor structure of the data. Factor analysis is not without cost, however. It is mathematically complicated and entails diverse and numerous considerations in application. Its technical vocabulary includes strange terms such as eigenvalues, rotate, factor space, simple structure, orthogonal, loadings, and communality. Its results usually absorb a dozen or so pages in a given report, leaving little room for a methodological introduction or explanation of terms. Add to this the fact that students do not ordinarily learn factor analysis in their formal training, and the sum is the major cost of factor analysis: most laymen, social scientists, and policy-makers find the nature and significance of the results incomprehensible. Factor analysis is a means by which the regularity and order in phenomena can be discerned. As phenomena co-occur in space or in time, they are patterned; as these co-occurring phenomena are independent of each other, there are a number of distinct patterns. Patterned phenomena are the essence of workaday concepts such as “table,” “chair,” and “house,” and at a less trivial level-patterns structure our scientific theories and hypotheses. We associate a pattern of attitudes, for example, with businessmen and another pattern with farmers. "Economic development" assumes a pattern of characteristics, as does the concept of "communist political system." The notion of morality itself embodies a pattern of elements. Factor analysis can be applied in order to explore a content area, structure a domain, map unknown concepts, classify or reduce data, illuminate causal nexuses, screen or transform data, define relationships, test hypotheses, formulate theories, control variables, or make inferences. Factor analysis is most familiar to researchers as an exploratory tool for unearthing the basic empirical concepts in a field of investigation. Representing patterns of relationship between phenomena, these basic concepts may corroborate the reality of prevailing concepts or may be as new and strange as to defy immediate labeling. Factor analysis is often used to discover such concepts reflecting unsuspected influences at work in a domain. The delineation of these interrelated phenomena enables generalizations to be made and hypotheses posed about the underlying influences bringing about the relationships. For example, if a political scientist were to factor the attributes and votes of legislators and were to find a pattern involving urban constituencies and liberal votes, he could use this finding to develop a theory linking urbanism and liberalism. The ability to relate data in a meaningful fashion is a prime aspect of induction and, for this, factor analysis is useful and efficient. Factor analysis may also be employed deductively, in two ways. One way is to elaborate the geometric or algebraic structure of factor analysis as part of a theory. Within the theory the factor analysis model can then be used to arrive at deductions about phenomena. The second deductive approach is to hypothesize the existence of particular dimensions and then to factor analyze the data to see whether these dimensions emerge (our first research hypothesis). Although factor analysis is not often used this way, the restraint is not due to methodology but to research tradition. If, as an example, scholars believe that ideology, power, and trade are the primary patterns of international behavior, then this proposition can be tested. Data can be collected on those variables that index international relations in its greatest diversity, and those specific variables distinguishing (by theory) the ideology, power, and trade patterns should be defined. To test whether these patterns actually exist is the factor analysis task.

  7. A Likert item is simply a statement which the respondent is asked to evaluate according to any kind of subjective or objective criteria; generally the level of agreement or disagreement is measured. Often five ordered response levels are used, although many psychometricians advocate using seven or nine levels; a recent empirical study found that a 5- or 7-point scale may produce slightly higher mean scores relative to the highest possible attainable score, compared to those produced from a 10-point scale, and this difference was statistically significant. In terms of the other data characteristics, there was very little difference among the scale formats in terms of variation about the mean, skewness or kurtosis. The format of a typical five-level Likert item is:

    1. 1.

      Strongly disagree

    2. 2.

      Disagree

    3. 3.

      Neither agree nor disagree

    4. 4.

      Agree

    5. 5.

      Strongly agree.

  8. “Since factor analysis incorporates analytic possibilities as a theory and empirical techniques for connecting the theory to social phenomena, its potentiality promise much theoretical development for the social sciences. Looking ahead for a century factor analysis and the complementary multiple regression model are initiating a scientific revolution in the social sciences as profound and far-reaching as that initiated by the development of the calculus in physics.” (Rummel 1988).

  9. A pattern, from the French patron, is a type of theme of recurring events or objects, sometimes referred to as elements of a set. These elements repeat in a predictable manner. It can be a template or model which can be used to generate things or parts of a thing, especially if the things that are created have enough in common for the underlying pattern to be inferred, in which case the things are said to exhibit the unique pattern. Pattern matching is the act of checking for the presence of the constituents of a pattern, whereas the detecting for underlying patterns is referred to as pattern recognition. The question of how a pattern emerges is accomplished through the work of the scientific field of pattern formation. The most basic patterns are based on repetition and periodicity. A single template, or cell, is combined with duplicates without change or modification. For example, simple harmonic oscillators produce repeated patterns of movement.

  10. A factor score is a numerical value that indicates a person's relative spacing or standing on a pattern (latent factor).

  11. An important technique for analyzing the effect of categorical factors (in our case the mechanism of moral engagement) on a response (in our case the professor’s factor scores on the established dimensions of moral thinking) is to perform an Analysis of Variance. An ANOVA decomposes the variability in the response variable amongst the different factors. Depending upon the type of analysis, it may be important to determine: (a) which factors have a significant effect on the response, and/or (b) how much of the variability in the response variable is attributable to each factor. A one-way analysis of variance (ANOVA) is used when the data are divided into groups according to only one factor. The questions of interest are usually: (a) is there a significant difference between the groups? And (b) If so, which groups are significantly different from which others?

  12. Professor’s patterns of moral thinking relative relations during their real life moral thinking, deciding and acting.

  13. These results are related with neurophysiological data about simultaneous activation of different brain locations during the process of moral thinking at the abstract level.

  14. Existing as an essential constituent or characteristic; involved in the constitution or essential character of something: belonging by nature or habit.

  15. The variance and the closely-related standard deviation are measures of how spread out a distribution is. In other words, they are measures of variability. The variance is computed as the average squared deviation of each number from its mean.

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Correspondence to Mladen Pečujlija.

Appendix

Appendix

See Tables 6 and 7.

Table 6 The professor’s affiliations
Table 7 EFA moral thinking patterns

The first pattern explains the 20.97% of total varianceFootnote 15 of the professor’s moral thinking at the abstract level and it consists of the three items from our questionnaire. The first item of this extracted pattern is: “I think that it is necessary to do to others what we would like them to do to us”; the second is: “It is necessary to do well regardless of its consequences for me”; the third is: “Moral person takes care of the interests of others as well”. With regard to the fact that these three items represent basically deontological moral orientation, we shall call this pattern of moral thinking at the abstract level DEONTOLOGICAL PATTERN.

Second pattern explains 17.88% of the total variance of the professor’s moral thinking at the abstract level. Three items from our questionnaire are projected on it. This pattern includes the following items: “It is enough to obey the law in order to be moral”; “Moral is what brings more good than evil”; and “There is a universal moral truth that we should all observe”. We named this pattern FORMAL PATTERN, given that the items that it includes have a formal character of observing the law in any given form. Third pattern explains 17.49% of total variance of the professor’s moral thinking at the abstract level and includes two items from our questionnaire. Its items are: “What is good for me is moral” and “Moral is a very subjective category, it is a matter of personal taste”. With regard to the nature of the statements, we shall call it SUBJECTIVE PATTERN. The exploratory factor analysis showed that during the process of professor’s moral thinking at the abstract level simultaneously are activated deontological, formal and subjective patterns of moral thinking.

The factor scores of the DEONTOLOGICAL PATTERN activation level in the process of moral thinking at the abstract level differ from one another significantly in activation and de-activation of the mechanism of moral control (F = 4.58, p = .011, df = 256). The professors that have a higher factor score (higher activation level) of this pattern in the process of moral thinking at the abstract level have a pronounced proactive moral behavior. The selective contextual activation or deactivation of the mechanism of moral control is not pronounced, while the professors with which the activation and deactivation is in part or absolutely determined by context score significantly lower (lower activation level) on this pattern during the process of moral thinking at the abstract level. It is interesting to note that the professors who partly activate and deactivate the mechanism of moral control score lower on this pattern of the moral thinking at the abstract level than those whose activation and deactivation of the mechanism of moral control is absolutely contextually determined (Graph 2).

Graph 2
figure 2

The Deontological Pattern activation level in the process of professor’s moral thinking at the abstract level in relation with their moral behavior over time

The factor scores of the FORMAL DIMENSION activation level in the process of the moral thinking at the abstract level differ from one another in statistically significant way in activation and deactivation of the mechanism of moral control (F = 2.96, p = .053, df = 256). The professors who score higher activation level of this pattern in the process of moral thinking at the abstract level have absolutely contextually determined activation and deactivation of the mechanism of moral control, while those who have pronounced proactive moral behavior score the lowest activation level of this pattern in the process of moral thinking at the abstract level (Graph 3).

Graph 3
figure 3

The Formal Pattern activation level in the process of professor’s moral thinking at the abstract level in relation with their moral behavior over time

The factor scores of the SUBJECTIVE PATTERN activation level differ from one another in statistically significant way in activation and deactivation of the mechanism of moral control (F = 4.27, p = .015, df = 256). The highest activation level of this pattern in process of moral thinking at the abstract level have the professors who have relatively selective activation and deactivation of mechanism of moral control, followed by the professors who nourish the proactive attitude, and the lowest activation level of this pattern belongs to the professors whose activation and deactivation of the mechanism of moral control is absolutely contextually determined (Graph 4).

Graph 4
figure 4

The Subjective Pattern activation level in the process of professor’s moral thinking at the abstract level in relation with their moral behavior over time

Research Instrument

Gender

  1. 1.

    Male

  2. 2.

    Female

Faculty

  • Academy of Arts

  • Faculty of Agriculture

  • Faculty of Economics

  • Faculty of Law

  • Faculty of Medicine

  • Faculty of Philosophy

  • Faculty of Sciences

  • Faculty of Sport and Physical Education

  • Faculty of Technical Sciences

  • Faculty of Technology

Moral is that which is good for me

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

I think that it is necessary to do others what we would like them to do to us

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

It is enough to obey the law in order to be moral

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

It is necessary to do well regardless of its consequences for me

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

Moral person takes care of the interests of others as well

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

Moral is a very subjective category, it is the matter of personal taste

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

Moral is what brings more good than evil

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

There is a universal moral truth that we should all observe

  1. 1.

    Strongly disagree

  2. 2.

    Disagree

  3. 3.

    Neither agree nor disagree

  4. 4.

    Agree

  5. 5.

    Strongly agree

Do you always act with respect to your moral stance?

  1. 1.

    Yes, always

  2. 2.

    Yes, mostly

  3. 3.

    Depends on the situation in which I find my self

  4. 4.

    Sometimes

  5. 5.

    Never

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Pečujlija, M., Ćosić, I. & Ivanišević, V. A Professor’s Moral Thinking at the Abstract Level Versus The Professor’s Moral Thinking in the Real Life Situation (Consistency Problem). Sci Eng Ethics 17, 299–320 (2011). https://doi.org/10.1007/s11948-009-9190-x

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