The working of any organization or community requires the guidance of several rule and norms, which all people subscribe to without favor or prejudice. Every culture has an implicit and explicit characteristic that defines how people behave within the same environment. Explicit attributes of culture refer to the observable and notable behaviors, rituals, expressions and symbols that are visible to every member of the society (Ahearne, 2009). Implicit qualities refer to the underlying values that are neither written nor expressed but are known by the members of the said society or organization (Ahearne, 2009). The implicit nature of culture determines what is deemed appropriate and inappropriate while the explicit qualities often differentiate one culture from the other.
The study considers a firm that undertakes mass production of certain commodities. The first example of an explicit quality of the firm’s culture is the written manifesto that excellence is the primary goal of when assessing product quality. Fundamentally, the quality is explicit due to the printing of posters in every part of the premises reminding employees of the need for excellence (Ahearne, 2009). Secondly, the use of organic materials in production in a bid to conserve the environment in the same firm is another explicit characteristic. Such a quality may be denoted by having the color green as the brand.
The first example of an implicit characteristic is the knowledge that the manager does not tolerate being interrupted in a meeting or in his private time. According to Ahearne (2009), implicit qualities are unique and effective due to lack of display and instead the covert nature of their applicability. Secondly, the unwritten rule that being the most environment-friendly employee can lead to a promotion is an example of an implicit characteristic of the company’s culture. Both examples show that there is no expression through the writing of the said norms, but employees understand the need to uphold those aspects of the company culture.
Question 2
Although different cultures have varying definitions for intelligence, the universal definition is the ability to use knowledge, experience, memory, imagination, understanding, and judgment to solve problems and adapt to new situations (Legg " Hutter, 2006). A person may be equipped with knowledge and all other factors mentioned above but still fail in certain circumstances where they do not know how to proceed. Such a scenario calls for intelligent behavior which refers to how a person conducts themselves in response to a question or a situation experienced for the first time or previously unknown. The connection between intelligence and intelligent behavior requires the manipulation of already known knowledge and experiences to adapt to the requirements of the new set of problems. Intelligence and intelligent behavior connect to form behavioral intelligence as the set of skills and critical thinking that occur in response to the new problem (Legg " Hutter, 2006).
One example of an intelligent behavior is asking students in a classroom to use their knowledge of what is appropriate and acceptable to create a set of rules for governing the entire school. In such a scenario, the rule and regulations may be relevant to the students but cannot make sense to the administrators. For example, if one of the rules is the total elimination of detention, other students may support due to having bad experiences while at detention. However, the administrators use a different thinking strategy where removing detention from the school policy can affect the ability of teachers to discipline students. The second example that is predicated on the same logic is a teacher creating a career path for a student based on evaluation and performance. The student may not understand the intelligence or the thinking process of the teacher because of having choices and needs about their future. Fundamentally, the teacher and the students have different knowledge and experiences and therefore different intelligent behaviors.
Question 3
A dichotomous variable is one that has a binary nature and has two possible values during observation or measurement. Considering a categorical research factor with n categories, there are two possible values of consideration representing the membership in every nth category ("Categorical IVs in MLR: Dummy Coding", 2018). Considering the psychological field, one example of a dichotomous variable is the possibility of a pass or fail of a person during a behavioral assessment episode. Primarily, the ability to conduct duties conclusively may be the factor of the study, and the possible values of measurement or observation are pass and fail. The second example in behavioral analytics is the rightness or wrongness of an action or an undertaking such as terminating the employment of an individual.
A continuous variable is different in that it has an indefinite number of possible values ("Continuous Random Variables", 2005). A continuous variable does not provide limitations to a factor of measurement, study or observation. For example, the height of students in a school can vary extensively and have a wide range. Furthermore, is the same factor of height can have a dichotomous variable with the values short and tall, the height is continuous because both shortness and tallness can have an infinite range. The second example is the sum of two sides of a dice. Given that the rolling two dice can result in different combinations and permutations, the variable of the sum of any two sides is infinite because of the many numbers on each dice. Primarily, continuous variables are the opposite of discrete variables which have a finite number of values for each measurement or observation ("Continuous Random Variables", 2005).
References
Ahearne, J. (2009). Cultural policy explicit and implicit: A distinction and some uses. International Journal of Cultural Policy, 15(2), 141–153.
Categorical IVs in MLR: Dummy Coding. (2018). University of North Carolina. Retrieved from http://www.unc.edu/~rcm/psy282/p282.lec20.pdf
Continuous Random Variables. (2005). Carnegie Mellon University. Retrieved from https://www.stat.cmu.edu/~cshalizi/36-220/lecture-7.pdf
Legg, S., " Hutter, M. (2006). A Collection of Definitions of Intelligence. Retrieved from http://www.vetta.org/documents/A-Collection-of-Definitions-of-Intelligence.pdf
