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Communication Theory/Uncertainty Reduction

Advances in Interpersonal Communication: Charles Berger, Richard Calabrese and Key Uncertainty Theorists
Since the mid-twentieth century, the concept of information has been a strong foundation for communication research and the development of communication theory. Information exchange is a basic human function in which individuals request, provide, and exchange information with the goal of reducing uncertainty. Uncertainty Reduction Theory (URT), accredited to Charles R. Berger and Richard J. Calabrese (1975), recognized that reducing uncertainty was a central motive of communication. Through the development of URT, these scholars pioneered the field of interpersonal communication by examining this significant relationship in uncertainty research.

Heath and Bryant (2000) state: “One of the motivations underpinning interpersonal communication is the acquisition of information with which to reduce uncertainty” (p. 153). The study of information is basic to all fields of communication, but its relation to the study of uncertainty in particular advanced theoretical research in the field of interpersonal communication. URT places the role of communication into the central focus, which was a crucial step in the development of the field of interpersonal communication. Berger and Calabrese (1975) note: “When communication researchers have conducted empirical research on the interpersonal communication process, they have tended to employ social psychological theories as starting points” (p. 99). The research underlying the theory and efforts made by other contemporaries marked the emergence of interpersonal communication research; with the development of URT, communication researchers began to look to communication for methods of greater understanding rather than theoretical approaches founded in other social sciences.

The History of Interpersonal Communication Research: A Brief Overview
Traditionally, communication has been viewed as an interdisciplinary field. Interpersonal communication is most often linked to studies into language, social cognition, and social psychology. Prior to the 1960s, only a modest amount of research was completed under the label of interpersonal communication. Heath and Bryant (2000) marked this time as the origin of the field of interpersonal communication: “Particularly since 1960, scholars adopted communication as the central term because they wanted to study it as a significant and unique aspect of human behavior” (p. 59).

The 1960s produced research that impacted the development of an interpersonal field. Research in psychiatry examined personality and the influence of relationships, finding that psychiatric problems were not only a result of self problems but a result of relational problems as well. Research trends in humanistic psychology and existentialism inspired the idea that relationships could be improved through effective communication (Heath & Bryant, 2000).

Research conducted under the title of interpersonal communication initially focused on persuasion, social influence, and small group processes. Theories explored the role of learning, dissonance, balance, social judgment, and reactance (Berger, 2005). Kurt Lewin, a forefather of social psychology, played a considerable role in influencing interpersonal research pioneers such as Festinger, Heider, Kelley, and Hovland.

By the 1970s, research interests began to shift into the realm of social interaction, relational development, and relational control. This was influenced by the research of such scholars as Knapp, Mehrabian, Altman, Taylor, Duck, Kelley, and Thibaut. During the later part of the decade and into the 1980s, the cognitive approaches of Hewes, Planalp, Roloff, and Berger became popular along with research into behavioral and communicative adaptation by Giles, Burgoon, and Patterson. Berger (2005) states: “these early theoretical forays helped shape the interpersonal comm research agenda during the past two decades” (p. 416).

Today, interpersonal communication tends to focus on dyadic communication, communication involving face-to-face interaction, or communication as a function of developing relationships. Research into interpersonal communication theory typically focuses on the development, maintenance, and dissolution of relationships. It has been recognized that interpersonal communication is motivated by uncertainty reduction (Berger & Calabrese, 1975). Since its introduction in the 1970s, uncertainty has been recognized as a major field of study that has contributed to the development of the field of communication as a whole. This chapter strives to focus on those theorists who pioneered the research of uncertainty reduction in communication. Their work is crucial to the development of the field of interpersonal communication and is central in our understanding of interpersonal processes.

Defining Uncertainty
Since uncertainty has been identified as an important construct, necessary to the study of communication, it would be beneficial to know when the concept originated, and how it has been defined and studied. One way to consider uncertainty is through the theoretical framework of information theory. Shannon and Weaver (1949) proposed that uncertainty existed in a given situation when there was a high amount of possible alternatives and the probability of their event was relatively equal. Shannon and Weaver related this view of uncertainty to the transmission of messages, but their work also contributed to the development of URT.

Berger and Calabrese (1975) adopted concepts from the information theorists as well as Heider's (1958) research in attribution. Berger and Calabrese (1975) expanded the concept of uncertainty to fit interpersonal communication by defining uncertainty as to the “number of alternative ways in which each interactant might behave” (p. 100). The greater the level of uncertainty that exists in a situation, the smaller the chance individuals will be able to predict behaviors and occurrences.

During interactions, individuals are not only faced with problems of predicting present and past behaviors, but also explaining why partners behave or believe in the way that they do. Berger and Bradac’s (1982) definition of uncertainty highlighted the complexity of this process when they stated: “Uncertainty, then, can stem from the large number of alternative things that a stranger can believe or potentially say”

Uncertainty plays a significant role when examining relationships. High levels of uncertainty can severely inhibit relational development. Uncertainty can cause stress and anxiety which can lead to low levels of communicator competence (West & Turner, 2000). Incompetent communicators may not be able to develop relationships or may be too anxious to engage in initial interactions. West and Turner (2000) note that lower levels of uncertainty caused increased verbal and nonverbal behavior, increased levels of intimacy, and increased liking. In interactions, individuals are expected to increase predictability with the goal that this will lead to the ability to predict and explain what will occur in future interactions. When high uncertainty exists it is often difficult to reach this goal.

Although individuals seek to reduce uncertainty, high levels of certainty and predictability can also inhibit a relationship. Heath and Bryant (2000) state: “Too much certainty and predictability can deaden a relationship; too much uncertainty raises its costs to an unacceptable level. Relationship building is a dialectic of stability and change, certainty and uncertainty” (p. 271). Therefore uncertainty is a concept that plays a significant role in interpersonal communication. The following theorists explore how communication can be a vehicle individuals utilize to reduce uncertainly.

Early Influences
The following theorists significantly contributed to the examination of uncertainty in communication. The influence of their work can be seen as reflected in the assumptions of Berger and Calabrese (1975).

Leon Festinger (1919-1989)
Leon Festinger studied psychology at the University of Iowa under the direction of Kurt Lewin. Lewin, one of the founders of social psychology and a pioneer in the research of group dynamics, had a substantial influence on the development of interpersonal communication. After graduation, Festinger initially worked at the University of Rochester, but in 1945 he followed Lewin to Massachusetts Institute of Technology and the Research Center for Group Dynamics. After Lewin's death, Festinger worked at the University of Michigan, Stanford University, and the New School for Social Research (Samelson, 2000).

Much of Festinger’s research followed his mentor Lewin and further developed Lewin’s theories. Several of Festinger's theories were highly influential on the emerging field of interpersonal communication and on the development of URT. Festinger is best known for the theories of Cognitive Dissonance and Social Comparison. Cognitive Dissonance Theory (CDT) attempted to explain how an imbalance among cognitions might affect an individual. Lewin foreshadowed CDT in his observations regarding attitude change in small groups (Festinger, 1982). CDT allows for three relationships to occur among cognitions: a consonant relationship, in which cognitions are in equilibrium with each other; a dissonant relationship, in which cognitions are in competition with each other; and an irrelevant relationship, in which the cognitions in question have no effect on one another (West & Turner, 2000). Cognitive Dissonance, like uncertainty, has an element of arousal and discomfort that individuals seek to reduce.

Social Comparison theory postulates that individuals look to feedback from others to evaluate their performance and abilities. To evaluate the self, the individual usually seeks the opinions of others who are similar to the self. This need for social comparison can result in conformity pressures (Trenholm & Jensen, 2004). Berger and Calabrese (1975) related social comparison to URT by stating that “Festinger has suggested that persons seek out similar others who are proximate when they experience a high level of uncertainty regarding the appropriateness of their behavior and/or opinions in a particular situation” (p. 107).

Festinger received the Distinguished Scientist Award of the American Psychological Association and the Distinguished Senior Scientist Award from the Society of Experimental Social Psychology. Festinger’s legacy is significant, and his theoretical influence can still be recognized in contemporary social science research. Aronson (in Festinger, 1980) stated, “It was in this era that Leon Festinger invented and developed his theory of cognitive dissonance, and in my opinion, social psychology has not been the same since” (p. 3).

Fritz Heider (1896-1988)
Fritz Heider earned his doctorate in philosophy from the University of Graz. During his time in Europe, Heider worked with many renowned psychologists such as Wolfgang Köhler, Max Wertheimer, and Kurt Lewin. Heider, like Festinger, recognized Lewin as a substantial impact on his life: “I want to pay tribute to [Lewin's] stimulating influence, which has affected much of my thinking and which is still strong even in this book, although it does not derive directly from his work” (Heider, 1958, p. vii). In 1929, Heider moved to the United States to work at Smith College and later the University of Kansas where he worked for the remainder of his life (Ash, 2000).

Heider’s 1958 publication, The Psychology of Interpersonal Relations, signified a major breakthrough in the study of interpersonal communication (Heath & Bryant, 2000). At this point, social psychologists like Heider expanded their research to focus on interpersonal relations as an important field of study. Though many social psychologists focused on behavior in interpersonal relations, their research served as a gateway for research examining communication in interpersonal relationships. Heider’s text provided one of the first forums for discussing relational phenomena.

Heider’s work reflected Lewin’s cognitive approach to behavior. Heider (1958) focused on theories in cognitive consistency, emphasizing that individuals prefer when their cognitions are in agreement with each other. Heider examined how individuals perceive and evaluate the actions and behaviors of others, a focus reexamined in Berger and Calabrese’s development of URT. Heider stated: “persons actively seek to predict and explain the actions of others” (Berger & Bradac, 1982, p. 29). Heider’s theory of “naïve psychology” suggested that individuals act as observers and analyzers of human behavior in everyday life. Individuals gather the information that helps them to predict and explain human behavior. “The naïve factor analysis of action permits a man to give meaning to action, to influence the actions of others as well as of himself, and to predict future actions” (Heider, 1958, p. 123).

When examining motivations in interpersonal relations, Heider (1958) found that effective significance is greatly determined by causal attribution. Heider states: “Thus, our reactions will be different according to whether we think a person failed primarily because he lacked the adequate ability or primarily because he did not want to carry out the actions” (1958, p. 123). The condition of motivation becomes the focus and is relied on for making judgments and also interpreting the action.

Heider was awarded a Guggenheim Fellowship, a Distinguished Scientific Contribution Award from the American Psychological Association, and was a fellow of the American Academy of Arts and Sciences. His influence continues to grow after his death in 1988.

Claude E. Shannon (1916-2001) and Warren Weaver (1894-1978)
Claude E. Shannon received his B.S. from the University of Michigan, Ann Arbor, and his Ph.D. from Massachusetts Institute of Technology (MIT). Shannon worked for the National Research Council, the National Defense Research Committee, and Bell Telephone Laboratories, where he developed the mathematical theory of communication, now known as information theory, with Warren Weaver. Shannon went on to teach at MIT until his death in 2001. During his lifetime Shannon was awarded the Liebmann Prize, Ballantine Medal, Who's Who Life Achievement Prize, and the Kyoto Prize (“Claude Elwood Shannon”, 2002).

Warren Weaver received his B.S. and Ph.D. from the University of Wisconsin. Weaver worked as faculty at Throop College, California Institute of Technology, University of Wisconsin, and served in World War One. Weaver was also an active member of the Rockefeller Foundation, Sloan-Kettering Institute for Cancer Research, Alfred P. Sloan Foundation, and Salk Institute for Biological Studies, serving in many leadership roles. He was awarded UNESCO's Kalinga Prize before his death in 1978 (Reingold, 2000).

Shannon and Weaver significantly contributed to the systematic approach to the study of communication. Both theorists were engineers who sought to explain information exchange through cybernetic processes. They were the first to effectively model information, as they sought to explain how to attain precise and efficient signal transmissions in the realm of telecommunications. In their theory of information, Shannon and Weaver (1949) showed that the need to reduce uncertainty motivates an individual’s communication behavior. This concept was later extended by Berger and Calabrese (1975) in the development of URT.

Information theory provided the connections from information to uncertainty and uncertainty to communication that facilitated the development of URT. “Shannon & Weaver’s (1949) approach stressed the conclusion that information is the number of messages needed to totally reduce uncertainty” (Heath & Bryant, 2000, p. 145). Individuals have a desire to reduce uncertainty and they are able to fulfill this need by increasing information. Individuals increase information through communication (Shannon & Weaver, 1949). These concepts are further explored in the examination of information-seeking strategies in URT.

Charles R. Berger: Biography
Charles R. Berger received his B.S. from Pennsylvania State University and his M.A. and Ph.D. from Michigan State University. After graduation, Berger worked at Illinois State University at Normal, Northwestern University, and the University of California at Davis, where he continues to work today as the chair of the Department of Communication. Berger has been involved with the International Communication Association since the 1970s, is an active member of the National Communication Association, and belongs to such professional groups as the American Psychological Society, the Society for Experimental Social Psychology, the Society for Personality and Social Psychology, and the Iowa Network for Personal Relationships (“Charles R. Berger”, 2001).

Berger has published on a variety of topics in interpersonal communication including uncertainty reduction, strategic interaction, information-seeking, attribution, interpersonal attraction, social cognition, and apprehension. In the past thirty-five years, Berger has published approximately forty articles appearing in the Communication Education, Communication Monographs, Communication Research, Communication Theory, Communication Quarterly, Communication Yearbook, Educational and Psychological Measurement, Human Communication Research, Journal of Communication, Journal of Consulting and Clinical Psychology Journal of Social Issues, Journal of Personality, Personal Relationship Issues, Speech Monographs, Western Journal of Communication, and the Western Journal of Speech Communication. Berger has coauthored five books and contributed to over thirty other texts. In 1982, Berger received the Golden Anniversary Book Award, presented by the Speech Communication Association, for his text: Language and Social Knowledge.

Richard J. Calabrese: Biography
Richard J. Calabrese received his B.A. from Loyola University, two M.A. degrees from Bradley University, and his Ph.D. from Northwestern University. Calabrese has taught at Bradley University, the University of Illinois at Urban, and Bowling Green University. Calabrese became a professor in communication at Dominican University in River Forest, Illinois, in 1967, where he continues to work today. Currently, Calabrese is the director of the Master of Science in Organization Management Program at Dominican University and also a consultant for organizational communication (“Richard Joseph Calabrese”, 2001).

Calabrese is a member of the International Association of Business Communicators, the Speech Communication Association, and is involved with the National Communication Association. Calabrese is the coauthor of Communication and Education Skills for Dietetics Professionals.

A Theory of Uncertainty Reduction: “Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication” (1975).
In 1971, Berger became an assistant professor of communication at Northwestern University. During this time, Calabrese studied under Berger, receiving his Ph.D. in 1973. In 1975, Berger and Calabrese published “Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication,” which serves as the foundation of URT. This article inspired a wave of new research examining the role of uncertainty in communication. Berger and Calabrese (1975) formed URT, also known as initial interaction theory, to explain the role of communication in reducing uncertainty in initial interactions and the development of interpersonal relationships.

The theory was developed, like other interpersonal theories before it (Heider, 1958), with the goal of allowing the communicator the ability to predict and explain initial interactions. Though Berger and Calabrese did not explore the realm of subsequent interaction, they did strongly recommend that future research should investigate the application of the framework of URT to developed relationships. Especially in initial encounters, there exists a high degree of uncertainty given that a number of possible alternatives exist in the situation (Shannon & Weaver, 1949). But individuals can use communication to reduce this uncertainty. Berger and Calabrese (1975) maintained that “communication behavior is one vehicle through which such predictions and explanations are themselves formulated” (p. 101). Individuals have the ability to decrease uncertainty by establishing predictable patterns of interaction. Because of this, reducing uncertainty can help foster the development of relationships.

Berger and Calabrese (1975) found that uncertainty was related to seven other communication and relational-focused concepts: verbal output, nonverbal warmth, information seeking, self-disclosure, reciprocity, similarity, and liking. From those concepts, the researchers introduced a collection of axioms, or propositions, supported by past uncertainty research. Each axiom states a relationship between a communication concept and uncertainty. From this basis of axioms, the theorists were able to use deductive logic to infer twenty-one theorems that comprise the theory of uncertainty reduction (West & Turner, 2000). The procedure used to develop the axioms and theorems was adopted from Blalock (1969). A complete list of the axioms and theorems of URT is available in Appendix A.

Central to URT is the supposition that in initial interactions, an individual’s primary concern is to decrease uncertainty and increase predictability regarding the behaviors of the self and the communicative partner. This idea is based on Heider's (1958) notion that individuals seek to make sense out of the events he perceives (Berger & Calabrese, 1975). Individuals must be able to engage in proactive and retroactive strategies to learn how to predict what will happen and also explain what has already happened.

Heath and Bryant (2000) stated: “Uncertainty-reduction theory is a powerful explanation for communication because it operates in all contexts to help explain why people communicate as they do” (p. 271). The impact of Berger and Calabrese (1975) on the field of interpersonal communication was and continues to be prolific. In the past thirty years, this article has generated a plethora of research, changing the way that relationships are explored and analyzed.

Expansions on Uncertainty Reduction
Although URT was primarily formed to explain behavior in initial interactions, its application has since been expanded to incorporate all levels of interpersonal relationships. “Uncertainties are ongoing in relationships, and thus the process of uncertainty reduction is relevant in developed relationships as well as in initial interactions” (West & Turner, 2000, p. 141). The following section will examine uncertainty reduction research since its introduction in 1975.

A. Charles Berger
Since its conception, Berger has produced a plethora of research expanding URT to better fit the dynamic nature of interpersonal relations. Berger (1979) established that three predeceasing conditions must exist for an individual to reduce uncertainty. These motivations to reduce uncertainty include the potential for costs or rewards, deviations from expected behavior, and the possibility of future interaction.

In 1982, Berger teamed up with James J. Bradac, formerly of the University of California at Santa Barbara (1980–2004), to publish a book devoted to uncertainty reduction research. Their text, titled Language and Social Knowledge: Uncertainty in Interpersonal Relations, was also edited by Howard Giles, the originator of Communication Accommodation Theory and also faculty of UCSB. In this text, the authors focused on the function of communication, and specific language, as a proponent for reducing uncertainty.

Berger and Bradac (1982) proposed six axioms that built on URT’s original seven axioms to extend the relationship between uncertainty reduction and language. Through the use of these axioms, the authors specifically examined the role of language as an uncertainty reducing agent. The authors further arranged uncertainty into two categories: cognitive uncertainty and behavioral uncertainty (Berger & Bradac, 1982). Cognitive uncertainty refers to the uncertainty associated with beliefs and attitudes. Behavioral uncertainty refers to uncertainty regarding the possible behaviors in a situation. This categorization helped researchers identify the origins of uncertainty, which resulted in an increased ability to address the discomfort produced by uncertainty.

Berger and Bradac were cognitive that URT would be more useful if its influence was extended to include developed relationships as well as initial interaction. Berger and Bradac (1982) alleviated this by stating that uncertainty reduction was critical to relational development, maintenance, and dissolution as well. Berger again related his research to Heider (1958) by stating that individuals make casual attributions regarding communicative behavior. As relationships further develop, individuals make retroactive and proactive attributions regarding a partner’s communication and behavior (Berger & Bradac, 1982).

Berger (1987) highlighted the role of costs and rewards in relationships by stating that “uncertainty reduction is a necessary condition for the definition of the currency of social exchange, and it is through the communicative activity that uncertainty is reduced” (Berger, 1987, p. 57). Berger (1987) also expanded URT by claiming that three types of information-seeking strategies are used to reduce uncertainty: passive, active, or interactive strategies. This is related to the concepts of information theory (Shannon & Weaver, 1949), emphasizing that increased information results in decreased uncertainty.

B. Developments from Other Researchers
The latter improvements made by Berger expanded the scope and value of URT. Other researchers also made contributions to further developments of URT. Since its introduction in 1975, URT has been expanded from a theory of relational development to one also important in established relationships. The following sections examine the contributions made by current interpersonal researchers to URT.

 * William Douglas
 * William Douglas was a student at Northwestern University while Berger was on faculty. The two scholars collaborated in their study of uncertainty in 1982, and Douglas continued in the same vein of research after graduation.  Douglas’ research has appeared in major communication journals including: Communication Monographs, Communication Research, Human Communication Research, Journal of Broadcasting and Electronic Media, and the Journal of Personal and Social Relationships.  Douglas’ research in uncertainty accounts for individual differences when examining initial interactions.  Much of his research expanded previous work in initial interaction, examined global uncertainty, self-monitoring, and the relationship of verbal communication to uncertainty reduction.
 * Douglas (1987) examined one of the motivations to reduce uncertainty originally posited in Berger (1979): the anticipation of future interaction. In this study, question-asking in situations of varying levels of anticipated future interaction was analyzed.  Douglas found that high levels of mutual question-asking occurred when the level of anticipated future interaction was moderate. This finding suggested that individuals seem to avoid negative consequences (Douglas, 1987).  Douglas (1990) expanded this verbal communication to uncertainty relationship by discovering that question-asking resulted in uncertainty reduction which in turn resulted in increased levels of disclosure.
 * Douglas (1991) defines global uncertainty as “uncertainty about acquaintanceship in general” (p. 356). In this article, Douglas found that individuals with high global uncertainty are less likely to engage in question-asking, self-disclosure, and are evaluated as less competent communicators than individuals with low global uncertainty.  Findings also suggested that high global uncertainty positively correlates to communication apprehension.  This has a negative effect on relational development and can result in low levels of relational satisfaction.

 * Uncertainty-Increasing Events: Sally Planalp and James Honeycutt (1985) also made substantial contributions to uncertainty reduction research. Planalp and Honeycutt recognized that communication does not always function as an uncertainty reducing agent, but can also serve to increase uncertainty when information conflicts with past knowledge.  The authors researched what specific events lead to increased uncertainty in interpersonal relationships and their effects on both the individual and the relationship.  The results found that uncertainty-increasing events were very likely to result in relational dissolution or decreased closeness of the relational partners.  This research was very beneficial because it led to better explanations regarding the role of communication in uncertainty reduction.

 * Romantic Relationships: Malcolm Parks and Mara Adelman (1983) sought to expand the breadth of URT to apply to romantic relationships. Data was collected from individuals in premarital romantic relationships through questionnaires and telephone interviews.  Individuals who communicated more often with their romantic partner and their partner’s network (family and friends) perceived greater similarity to their partner.  They also received greater support from their own network (family and friends) and experienced a lower degree of uncertainty (Parks & Adelman, 1983).  These findings support URT’s axioms that greater verbal communication and similarity serve to decrease uncertainty (Berger & Calabrese, 1975), and also extend the scope of URT to romantic relationships.

 * Relational Maintenance: In recent years, studies have begun to link uncertainty reduction to relational maintenance processes. Dainton and Aylor (2001) connected relational uncertainty positively to jealousy and negatively to relational maintenance behaviors.  These results suggested that individuals are less likely to engage in relational maintenance when high uncertainty exists in the relationship.
 * Cultural Studies: Research conducted by William Gudykunst and Tsukasa Nishida (1984) expanded URT’s scope to intercultural contexts. Specifically, the researchers examined the effects of attitude similarity, cultural similarity, culture, and self-monitoring on attraction, intent to interrogate, intent to self-disclose, attributional confidence, and intent to display nonverbal affiliative behaviors (Gudykunst & Nishida, 1984).   Research conducted on individuals of the Japanese and American cultures found a positive correlation between each of the variables indicating that uncertainty varies across cultures.

C. Criticisms of URT
Berger (1987) recognized that URT “contains some propositions of dubious validity” (p. 40). Like many other successful theoretical approaches, Berger and Calabrese’s (1975) theory of uncertainty reduction has inspired subsequent research that served both as supporting evidence and in an oppositional role to the theory. These criticisms help to clarify the underlying principles of the theory and suggest ways for improvement for future research.

Michael Sunnafrank (1986) argued that a motivation to reduce uncertainty is not a primary concern in initial interactions. His belief was that a “maximization of relational outcomes” (p. 9) was of more significant concern in initial encounters. Sunnafrank argued that the predicted outcome value (POV) of the interaction had a greater effect on uncertainty. Berger (1986) combated Sunnafrank’s arguments by acknowledging that outcomes cannot be predicted if there is no previous history of interaction regarding the behavior of the individuals. Berger claims that Sunnafrank’s arguments simply expanded URT: that by predicting outcomes (using POV) individuals are actually reducing their uncertainty (Berger, 1986).

Kathy Kellermann and Rodney Reynolds (1990) also tested the validity of the URT. Their primary concern was axiom three, which related high uncertainty to high information seeking (see appendix A). Their study of over a thousand students found that want for knowledge was a greater indicator than a lack of knowledge for the promotion of information-seeking (Kellermann & Reynolds, 1990). These researchers emphasized that high uncertainty does not create enough motivation to result in information-seeking; rather want for information must also exist.

Canary and Dainton (2003) explored uncertainty reduction in terms of relational maintenance across cultural contexts and found that the applicability of URT may not hold to multiple cultures. Canary and Dainton (2003) focused on the concept of uncertainty avoidance in cultures stating: “individuals from cultures with a high tolerance for uncertainty are unlikely to find the experience of uncertainty as a primary motivator for performing relational maintenance” (p. 314). This leads to a general questioning of the validity of URT other cultures.

Legacy and Influence
Research has found that communication plays a critical role in initial interactions and relational development. Berger and Calabrese (1975) were the first to investigate the role of communication in initial interactions with the development of a theory of uncertainty reduction. Its widespread influence led to its adoption in other relational and communicative contexts such as small groups, mass communication, and computer-mediated communication.

The influence of URT is well noted by others in the field: “Postulates by Berger and Calabrese prompted more than two decades of research to prove, clarify, and critique uncertainty reduction’s explanation of how people communicate interpersonally” (Heath & Bryant, 2000, p. 275). Berger and Calabrese (1975) generated additional studies on uncertainty reduction accomplished by such scholars as Hewes, Planalp, Parks, Adelman, Gudykunst, Yang, Nishida, Douglas, Kellerman, Hammer, Rutherford, Honeycutt, Sunnafrank, Capella, Werner, and Baxter. URT has withstood the test of time, proving itself as a heuristic theory with the utility that increases with subsequent research.

Axioms of Uncertainty Reduction Theory

 * 1) Given the high level of uncertainty present at the onset of the entry phase, as the amount of verbal communication between strangers increases, the level of uncertainty for each interactant in the relationship will decrease. As uncertainty is further reduced, the amount of verbal communication will increase.
 * 2) As nonverbal affiliative expressiveness increases, uncertainty levels will decrease in an initial interaction situation. In addition, decreases in uncertainty level will cause increases in nonverbal affiliative expressiveness.
 * 3) High levels of uncertainty cause an increase in information-seeking behavior. As uncertainty levels decline, information-seeking behavior decreases.
 * 4) High levels of uncertainty in a relationship cause decreases in the intimacy level of communication content. Low levels of uncertainty produce high levels of intimacy.
 * 5) High levels of uncertainty produce high rates of reciprocity. Low levels of uncertainty produce low reciprocity rates.
 * 6) Similarities between persons reduce uncertainty, while dissimilarities produce increases in uncertainty.
 * 7) Increases in uncertainty level produce decreases in liking; decreases in uncertainty level produce increases in liking.

Theorems of Uncertainty Reduction Theory

 * 1) Amount of verbal communication and nonverbal affiliative expressiveness are positively related.
 * 2) Amount of communication and intimacy level of communication are positively related.
 * 3) Amount of communication and information seeking behavior are inversely related.
 * 4) Amount of communication and reciprocity rate are inversely related.
 * 5) Amount of communication and liking are positively related.
 * 6) Amount of communication and similarity are positively related.
 * 7) Nonverbal affiliative expressiveness and intimacy level of communication content are positively related.
 * 8) Nonverbal affiliative expressiveness and information seeking are inversely related.
 * 9) Nonverbal affiliative expressiveness and reciprocity rate are inversely related.
 * 10) Nonverbal affiliative expressiveness and liking are positively related.
 * 11) Nonverbal affiliative expressiveness and similarity are positively related.
 * 12) Intimacy level of communication content and information seeking are inversely related.
 * 13) Intimacy level of communication content and reciprocity rate are inversely related.
 * 14) Intimacy level of communication content and liking are positively related.
 * 15) Intimacy level of communication content and similarity are positively related.
 * 16) Information seeking and reciprocity rate are positively related.
 * 17) Information seeking and liking are negatively related.
 * 18) Information seeking and similarity are negatively related.
 * 19) Reciprocity rate and liking are negatively related.
 * 20) Reciprocity rate and similarity are negatively related.
 * 21) Similarity and liking are positively related.


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Talk:Portuguese/Online resources

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I'm afraid the soundfiles at http://languagelab.bh.indiana.edu/default.htm

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Talk:Communication Theory/Uncertainty Reduction

Robert Lawrence Heath
In the 3rd chapter on "uncertainty reduction" 2nd's paragraph you mention an author Health. The author's name is not Health but Heath.
 * Fixed it, thanks for pointing it out. (That's something you could have fixed yourself, also!) TDang (discuss • contribs) 17:07, 12 October 2011 (UTC)


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Georgia Water/External Links/People

/Instructions/ for adding your name to the roster below.

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 * | Alber, Merryl . . . . University of Georgia, | Marine Sciences, Athens

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 * Bennett, David . . . . | Georgia Soil and Water Conservation Commission, Athens
 * | Bethea, Sally S.. . . . | Upper Chattahoochee Riverkeeper, Atlanta

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 * | Donaghue, Robert (Bob). . . . | Georgia DNR Pollution Prevention Assistance Division, Atlanta

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/Kathryn J. Hatcher/ - .... | University of Georgia

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User:PTNFromm

Hi! --PTNFromm 18:03, 27 October 2005 (UTC)

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User talk:PTNFromm

Have a nice day! --PTNFromm 18:04, 27 October 2005 (UTC)

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XML - Managing Data Exchange/Business Intelligence and XML/Answers

=1. Business Intelligence and XML (Answers)=

Exercise 1
The end user wants to read the report in Japanese language, so you have to add a variable for Japanese language.


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Talk:Materials Science

This is a book that will be written by me mfadock, edit at leisure. each section will follow how i am currently being taught. i will draw diagrams in gimp and upload them. i will steal from wherever is nessisary (gpl'ed texts), and include problem sets along with solutions. as this is materials science, i would advocate different levels of material, levels 1-5 with increasing difficulty. --Mfadock 20:00, 27 October 2005 (UTC) - email me with suggestions or leave something here. ps. im new at this, so it wont be easy on me.

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 * Material
 * Composite material
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 * Concrete
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title: Talk:Materials Science


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User talk:Snowhare~enwikibooks

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Unfortunately, your account clashes with another account also called Snowhare. To make sure that both of you can use all Wikimedia projects in future, we have reserved the name Snowhare~enwikibooks that only you will have. If you like it, you don't have to do anything. If you do not like it, you can pick out a different name.

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Sorry for the inconvenience.

Yours, Keegan Peterzell Community Liaison, Wikimedia Foundation 23:42, 17 March 2015 (UTC)

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title: User talk:Snowhare~enwikibooks


text:
Materials Science

Materials science is the study of the structural and functional properties of materials. It focuses on the factors inherent within materials that influence their properties. These factors include composition, the structure of the matter within the material and the type and quantity of defects that are present. It is a multidisciplinary subject that draws upon and feeds back to the learning in just about every field of science and engineering in some way or another placing the subject in a central role to many of the activities in these related subjects.

This book is aimed at those studying materials science at the undergraduate level in university whether as their major field or as a single module of a related engineering course.

Contents

 * 1) /Introduction/
 * 2) /Structure of Matter/
 * 3) /Defects and Microstructure/
 * 4) /Diffusion/
 * 5) /Mechanical Properties/
 * 6) /Material Processing/
 * 7) /Thermodynamics/
 * 8) /Materials/
 * 9) /Material Characterization/
 * 10) /Thermochromics/
 * 11) /Crystallography/
 * 12) /Biocompatible Material/
 * 13) /Analytical Techniques/
 * 14) /Useful Formulas/

title: Materials Science


text:
User:Gdd

Y helo thar.

Meta: gdd

title: User:Gdd


text:
Digital Circuits/Logic Operations

In the previous chapter we learned what digital information is. Digital information is represented as bits, which can take on values of either 1 or 0. In this chapter we begin to explore how to perform calculations and do other work using digital information.

Much of what we will be discussing was formalized by George Boole (1815–1864) in his paper An Investigation of the Laws of Thought, on Which Are Founded the Mathematical Theories of Logic and Probabilities, published in 1854. It had few applications at the time, but eventually scientists and engineers realized that his system could be used to create efficient computer logic. The branch of mathematics involving digital logic is aptly named Boolean Algebra.

Basic Operators
Digital logic has three basic operators, the AND, the OR and the NOT. These three operators form the basis for everything in digital logic. In fact, almost everything your computer does can be described in terms of these three operations. Fortunately, these operations are not difficult to understand, as their meanings resemble the meanings of the words as used in every day language.

AND
The symbol for an AND operator is a single dot. A mathematical expression using AND looks like this.

$$A \cdot B$$

Alternate notations for AND are $$ AB, A*B, A $$ && $$ B $$ and $$ A \land B.$$ The value of an AND expression is 1 only if both input values are 1. Otherwise, the value is 0. That is, the above expression equals 1 if and only if A and B are 1. The AND operator can be described with the following truth table.

OR
The symbol for the OR operator is a plus sign. A mathematical expression using OR looks like this.

$$A + B$$

Alternate notations for OR are A$$\vee$$B, A OR B and A || B. The value of an OR expression is 0 only if both the input values are 0. Otherwise the values is 1,that is the above expression equals only if A and B is 0. The truth table for the OR operator

NOT
NOT is a unary operator, which requires only single input, while as AND and OR are binary operators as they require two values as input. Symbol for NOT operator. $$\overline{A}$$ or A'

The value of a NOT expression is the opposite value of the input value.

NAND and NOR
If the AND, OR and NOT operators are combined, then the NOR and NAND can be created:
 * A NAND B is $$\overline{A \cdot B}$$. This is the inverted output of the AND gate.
 * A NOR B is $$\overline{A+B}$$. This is just the inverted output of an OR gate.

XOR and XNOR
Two other important gates are the exclusive-OR and exclusive -NOR operators, XOR and XNOR. This is sometimes denoted by a plus sign in a circle.
 * A XOR B is $$\overline{A} \cdot B + A \cdot \overline{B} = A \oplus B $$. This is true only if exactly one of the inputs is one.
 * A XNOR B is $$\overline{\overline{A} \cdot B + A \cdot \overline{B}} = \overline{A \oplus B}$$. This is the inverted output of an XOR gate: it is only true if both input are the same.

XOR represents a modulo-2 addition, which means that if you add 1 to 1, you wrap around back to 0. This is very useful function in digital electronics, but it is not an important concept in Boolean algebra.

Formal Mathematical Operators
In the field of logic, which is part of discrete mathematics, there is an alternative notation to the addition/multiplication type we have seen:

 * AND is represented by $$\wedge$$ Therefore A AND B would be $$A \wedge B$$.
 * OR is represented by $$\vee$$ Therefore A OR B would be $$A \vee B$$.
 * NOT is represented by $$\lnot$$. Therefore NOT A is $$\neg A$$.

Unfortunately, computer science, engineering and mathematics seem unable to establish a consensus, so we are stuck with both forms of notation. Other books, and especially those that deal more with pure logic or discrete mathematics may have various notations, so if other books are consulted, then the other notation needs to be known. As this is an engineering book, we will not use this notation.

Boolean Algebra Laws
Boolean Algebra, like regular algebra, has certain rules. These rules are Associativity, Distributivity, Commutativity and De Morgan's Laws. Associativity, Commutativity and Distributivity only apply to the AND and OR operators. Some of these laws may seem trivial because you are so used to them. However, when Boolean algebra was created with its different rules, every axiom we take for granted in "normal" algebra no longer was guaranteed to apply. These laws have been proved to hold under Boolean algebra.

Associativity
Associativity is the property of algebra that the order of evaluation of the terms is immaterial.

 * $$A+(B+C) \iff (A+B)+C \,$$
 * $$A \cdot(B \cdot C) \iff (A\cdot B) \cdot C \,$$

Distributivity
Distributivity is the property that an operator can be applied to each of the terms within the brackets.

 * $$A \cdot (B+C) \iff (A \cdot B)+(A \cdot C) \,$$
 * $$A+(B \cdot C ) \iff (A+B) \cdot (A + C) \,$$

Commutativity
Commutativity is the property that order of application of an operator is immaterial.
 * $$A \cdot B \iff B \cdot A \,$$
 * $$A+B \iff B+A \,$$

De Morgan's Law
De Morgan's Law is a consequence of the fact that the NOT or negation operator is not distributive.

 * $$\overline{P \cdot Q} \iff \overline {P}+ \overline {Q}$$
 * $$\overline{P+Q} \iff \overline {P} \cdot \overline {Q}$$

De Morgan's laws (named after Augustus De Morgan, 1806–1871) tell us: a NAND gate gives the same output as an OR gate with inputs complemented; a NOR gate gives the same output as an AND gate with inputs complemented. These complemented-input gates are also known as bubbled gates because of the way that they are indicated on a symbol, i.e., by including a small 'bubble' on each input, in the same fashion that circles are drawn on the outputs of the NOT, NAND and NOR gates.

De Morgan's laws are the most useful while simplifying a boolean expression. An easy way to remember these laws is "Change the sign, break the line".

Operator precedence
It is important to note that
 * $$A \cdot B+C \ne A \cdot (B+C)$$

This can be seen as either AND having a higher precedence or the fact that associativity does not hold between AND and OR or that it is an invalid application of distributivity.

Another way of looking at this is the application of our understanding of normal algebra, where the analogy between OR being addition and AND being multiplication is made. We would never make this error if this were normal algebra with numbers rather than Boolean entities.

Other Rules
All of these laws result in a number of rules that apply to all Boolean expressions. These laws have names, but it is only important that you are able to apply them where needed! Note that many rules have two forms - this called duality, and we will discuss it later.

Principle of Duality
The principle of duality tells us: If, in a boolean equation, we interchange the AND and OR operators and interchange '0' with '1' then the resultant boolean equation is also true.

 * Example 1:
 * If we are aware that A·(B+C)=(A·B)+(A·C) (law of distributivity of the AND operator) then by the principle of duality, we can say that A+(B·C)=(A+B)·(A+C) (law of distributivity of the OR operator).

 * Example 2:
 * Consider the identity law for the OR operator: A+0=A . Applying duality, we get the identity law for the AND operator: A·1=A.

Boolean Simplification
It is often the case that you want to simplify a given Boolean function. For example, you might want to reduce the number of logic gates required to implement that particular function. Simplification is done by repeated application of the rules and laws of Boolean algebra. Bear in mind that you sometimes have to apply them backwards to get the minimal form. NAND, NOR, XOR and XNOR all need to be expanded to just AND, OR and NOT in order for simplification to work.

Karnaugh Maps are a more formal way of doing this for the guaranteed smallest form, but we will do it by hand for now.

Examples
Simplify the following expressions.
 * 1) $$B \cdot A \cdot \overline {A}$$
 * 2) $$A \cdot \overline {B} + A \cdot B$$

Example 1

 * $$B\cdot A \cdot \bar {A} = B\cdot 0 $$  by rule 4b.
 * $$B\cdot A \cdot \bar {A} = 0 $$   using rule 5 applied to the result from the previous line.

So $$B \cdot A \cdot \bar {A} = 0$$

Example 2
Using distributivity, we can take A out of the brackets, giving
 * $$A \cdot (\overline{B} + B)$$

Using rule 4a, we see that:
 * $$A \cdot 1 = A$$

We therefore see that $$A \cdot \overline {B} + A \cdot B = A$$

title: Digital Circuits/Logic Operations


text:
User talk:128.138.177.109

Please stop. If you continue to vandalize pages, you will be blocked from editing Wikibooks.

title: User talk:128.138.177.109


text:
User talk:Cnelson~enwikibooks

Your account will be renamed
Hello,

The developer team at Wikimedia is making some changes to how accounts work, as part of our on-going efforts to provide new and better tools for our users like cross-wiki notifications. These changes will mean you have the same account name everywhere. This will let us give you new features that will help you edit and discuss better, and allow more flexible user permissions for tools. One of the side-effects of this is that user accounts will now have to be unique across all 900 Wikimedia wikis. See the announcement for more information.

Unfortunately, your account clashes with another account also called Cnelson. To make sure that both of you can use all Wikimedia projects in future, we have reserved the name Cnelson~enwikibooks that only you will have. If you like it, you don't have to do anything. If you do not like it, you can pick out a different name.

Your account will still work as before, and you will be credited for all your edits made so far, but you will have to use the new account name when you log in.

Sorry for the inconvenience.

Yours, Keegan Peterzell Community Liaison, Wikimedia Foundation 23:06, 17 March 2015 (UTC)

Renamed
 This account has been renamed as part of single-user login finalisation. If you own this account you can |log in using your previous username and password for more information. If you do not like this account's new name, you can choose your own using this form after logging in: . -- Keegan (WMF) (talk) 04:48, 19 April 2015 (UTC)

title: User talk:Cnelson~enwikibooks


text:
User talk:169.244.70.148

http://en.wikibooks.org/w/index.php?title=Blender_3D:_Noob_to_Pro/Blender_Windowing_System&curid=18497&diff=266870&oldid=259385

Vandalism
Please stop adding nonsense to Wikibooks. It is considered vandalism. If you would like to experiment, use the sandbox. Thank you. -- LV (Dark Mark) 14:57, 2 December 2005 (UTC)

 * Blocked for a year as hacker server (SORBS). --Derbeth talk 16:58, 2 December 2005 (UTC)

 * I belive this information is Completely Wrong. I happen to knwo that this IP is used by the Maine State Library Network, and I have to put an unblock request on my Wikipedia User talk page to edit several times.--Ac1983fan 22:52, 10 June 2006 (UTC)

title: User talk:169.244.70.148


text:
Talk:Latin/Lesson 9-Revision

Subjunctive ^_^
It's actually quite simple.

The present tense through future tenses use the present stem. I'm using the word amo, amare, amavi, amatus - to love, so the present stem is "am".

Present:

1st person: amor                         1st person (pl): amamur

2nd person: amaris                       2nd person (pl): amamini

3rd person: amatur                       3rd person (pl): amantur

Imperfect:

1st person: amabar                         1st person (pl): amabamur

2nd person: amabaris                       2nd person (pl): amabamini

3rd person: amabatur                       3rd person (pl): amabantur

Future:

1st person: amabor                         1st person (pl): amabimur

2nd person: amaberis                       2nd person (pl): amabimini

3rd person: amabitur                       3rd person (pl): amabuntur

For the perfect verbs, use the fourth principle part. Then, add the correct form of "to be". For perfect, you use the present to-be verb (sum, es, est...). For pluperfect, you use the imperfect (eram, eras, erat...) and for future perfect, you use the future tense. (ero, eris, erit)We're continuing with amo. Don't forget to make the usual "us" ending of your verb into an "i" when you're doing plurals.

Perfect:

1st person: amatus sum                      1st person (pl): amati sumus

2nd person: amatus es                        2nd person (pl): amati estis

3rd person: amatus est                       3rd person (pl): amati sunt

Pluperfect:

1st person: amatus eram                      1st person (pl): amati eramus

2nd person: amatus eras                      2nd person (pl): amati eratis

3rd person: amatus erat                      3rd person (pl): amati erant

Future Perfect:

1st person: amatus ero                       1st person (pl): amati erimus

2nd person: amatus eris                      2nd person (pl): amati eritis

3rd person: amatus erit                      3rd person (pl): amati erunt

Hope this is all correct and helps!

title: Talk:Latin/Lesson 9-Revision


text:
Visual Basic .NET/Collections

VB.NET supports a number of data structures called Collections. Collection can be either zero or one based, depending on how they are declared. A collection is similar to an array in that it can store multiple data entries. However, most collections have advanced methods associated with them that distinguish them from Arrays. Some of these collections are:

ArrayList
An ArrayList is a dynamic array, the size increases and shrinks when needed and stores elements as generic Object's, this provides us with the ability to store objects with differing types.

Add method
To add objects to the ArrayList use the System.Collections.ArrayList.Add(Object) method The following is an example of adding String objects to an Arraylist.

Queue
A queue is a first-in/first-out style collection. A queue has two unique methods used to enqueue and dequeue information from it. Using the System.Collections.Queue.Enqueue method, an object can be added to the end of the collection. Items can later be removed using the System.Collections.Queue.Dequeue method. This method will take the first object in the queue collection and then remove it from that collection.

Stack
A stack is a last-in/first-out style collection. A stack has three unique methods used to store and retrieve information from it. Using the System.Collections.Stack.Push method, an object can be added to the top of the stack, pushing the objects below it lower into the stack. Items can later be removed from the stack using the System.Collections.Stack.Pop method. This method will return the object at the top of the stack and remove it from the stack. Another method, System.Collections.Stack.Peek, is similar to the Pop method except it returns the object without removing it from the stack.

SortedList
A SortedList collection is a collection of objects that are sorted both by index (similar to an array) and by key. A key works in a manner similar to that of an index; however, unlike an index, a key can be any object.

Generics
Generics provide data structures that work for a variety of data types. While the collections discussed above store items as objects, generic collections store the values in a more specific type such as String or Integer.

List
A List(Of Type) allows a set of values to be accessed by index or as a collection. You can therefore mix array and collection syntax on the same set:

Visual Basic .NET/Collections

title: Visual Basic .NET/Collections


text: User talk:200.163.79.175

title: User talk:200.163.79.175


text:
Puzzles/Logic puzzles/Niki the Robot

Puzzles | Logic puzzles | Niki the Robot

Niki, the robot, lives on a chessboard with 8 by 8 squares. At any time Niki has a defined orientation looking either west (<), north (^), east (>) or south (v) and uniquely lives on one of the squares. Niki can be programmed by a sequence of the following commands:

move'n'pick Moves one square in the current direction and picks up an item, if present. Items are denoted with '*' on the board.

turn right Changes the direction of niki clockwise.

goto LABEL if wall LABEL can designate the position of any of the commands listed before this one in the program, i.e. the branch can only be upwards in the program. The command branches there if right ahead of Niki there is a wall, which means the border of the board or a wall between squares denoted with 'W'. Otherwise the next command is being executed.

If Niki moves and a wall is ahead, nothing happens.

Problem 1
Niki looks east.

-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --

The task is to pick up all items on the board.
 * Find a solution at all.
 * What is the smallest program (in terms of number of instructions) to perform the task?
 * What is the fastest program (in terms of the number of instructions that are executed)?

title: Puzzles/Logic puzzles/Niki the Robot


text:
Talk:Linux Guide/Linux commands

 * Most of these commands don't have anything to do with Bash. They are just command line programs that can run in any shell (like ksh or tcsh). --SamSam 01:06, 28 October 2005 (UTC)
 * A few of them are Bash or Bourne shell builtins. --Kernigh 03:44, 28 October 2005 (UTC)

Merge/move proposal
I suggest merging this into Guide to UNIX/Commands, where I am already contributing. It already has some Linux-specific commands (lsmod, modprobe) and at least one builtin command (cd). One idea might be to move this page to Guide to UNIX/Commands/Index, then wait for contributors to link commands to their descriptions. --Kernigh 03:44, 28 October 2005 (UTC)
 * FOR - it's just duplication really --H2g2bob 22:01, 25 January 2006 (UTC)
 * Against - the resulting article would be too long. -- CFeyecare   Talk!   19:07, 3 November 2008 (UTC)

Man to wiki
Since the man pages for the gnu commands are also GPL, is it reasonable to have a bot creating wiki pages from man pages? --SamSam 20:43, 28 October 2005 (UTC)

 * Most of the GNU "man" manuals (like ls) refer you to the "info" manuals (like coreutils). By the texinfo source of the coreutils manual, I read, Permission is granted to copy, distribute, and/or modify this document under the terms of the GNU Free Documentation License... with no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts. This statement seems compatible with Copyrights.

 * At one point I considered taking text from the coreutils manual to fill in missing commands for Guide to UNIX/Commands. I decided against this. Instead, I am planning to make links to the coreutils manual on GNU's web site, the various *BSD manual pages, and the Linux Questions wiki.

 * However, you, or other contributors, might take text from GNU manuals. In this case, the GFDL section 4 item I seems to require the creation of a "History" section describing how the GNU version and then the modified Wikibooks version was made. (If you, or other contributors, do not want to modify the GNU manual text, but want it in wiki format, then Wikisource might be a better place.)

 * However, many GNU manuals contain Invariant Sections or Cover Texts. In these cases, they seem to be incompatible with Copyrights, and cannot be used on Wikibooks. This includes the gcc and emacs manuals. --Kernigh 00:00, 29 October 2005 (UTC)

commands
i'm unshure that they belongs to coreutils but i've founded on all my systems(gentoo,qtopia embedd,knoppix)

-wget (downloader)

-losetup(link a file to a dev in order to mount loop files (ex:/knoppix.img to /dev/loop/0))

-md5sum

enchement proposal
why not making a command line tutorial with the folowing things: the | that is a pipe the > that write the data to a file etc... and a link to a bash script programing guide at the end of this book and use this guide as in introduction for the bash script programing guide

title: Talk:Linux Guide/Linux commands


text:
Wikijunior talk:South America/Venezuela

Little Venice
I recently watch a video called "Venezuela: Petroleum Powered Economy" (Princeton, NJ: Films for the Sciences and Humanities, 1992) in which the narator states that Vespucci named the country Venezuela "little Venice" because he saw people in Lake Maracaibo controling their boats with long poles like how they do in Venice. Adrian 04:12, 18 November 2006 (UTC)

 * How can you have one third plus two thirds PLUS four percent of the population ?!? A population of 104% it's too much, isn't?

1/3 and 2/3 are understood as approximate. It's not like it's a big deal. "every year 21 babies are born" was a big deal until I figured out that was for every 1000 population, which was not obvious from the way it was phrased. A much, much bigger deal was the 81% of the population works, which is just dumb. That's simply not the way employment statistics works. Just because there's 18% unemployment doesn't mean there's 81% employment, let alone that 81% of the population works.

And this is to say nothing of the white supremacist racism which I've ripped out of there pronto. Or the revisionist "Hugo Chavez is responsible for the actions of his enemies" which just makes me want to puke. 70.26.56.242 20:51, 6 November 2005 (UTC)

 * History of Venezuela --Kernigh 01:35, 30 November 2005 (UTC)

I have made some changes but this is so badly written with so many silly generalizations that it will be time consuming. Others come help please!!!!

title: Wikijunior talk:South America/Venezuela


text:
Wikijunior:Solar System/About weight and gravity

You may've read or heard people say that your weight would be different on the Moon, or on other planets and their moons. Does this mean that when you leave the Earth you somehow become fatter or thinner, without gorging on food or going on a diet? Hopefully you'll be glad to hear the answer is no! Here's why:

Gravity
Have you ever wondered why everything on the Earth doesn't just float up into the sky and off into space? Or perhaps why you land back on the ground whenever you jump up?

So far as we know, everything in the Universe tries to pull on everything else. This pull is what's known as gravity. It's actually very weak, but the more bulky things are and the nearer they are to each other, the stronger the pull becomes. The more bulky something is, the more it pulls on other things around it.

Compared to [each of us], the Earth is very bulky, so its pull on [each one of us] is very strong. That's why we don't all float away from the Earth – and why, whenever we jump up, we're pulled back down to the ground. We each pull on the Earth, just as it pulls on [each of us]. [Each of us] is tiny compared to the Earth, though, so our pull on the Earth is tiny too.

Other places in our Solar System [– and in the rest of the Universe –] are much more bulky than the Earth, while others are much less bulky than the Earth, so

{Still too complicated / sentences too long:} Other places in our Solar System and the rest of the universe are more or less bulky than the Earth, so their gravity is more or less than that here on Earth. So, if we leave the Earth and visit them, their pull on us will be more or less than that we know here on Earth. The Moon, for example, is less bulky than the Earth. If you weighed yourself there with a bathroom scale, it would say you weighed less than when you weighed yourself with it on the Earth. This is why people say your weight is different at different places in the Solar System or the rest of the universe! You haven't changed – what's changed is the strength of the gravity keeping you on the surface of whatever place you're visiting.

{Mention planet and comet formation?} {Perhaps even some simple(!) imagery to suggest curved space (without using that phrase) in place of "pull/ing"?}

Orbits and weightlessness
You don't even have to travel that far from the Earth to experience this change. If you travel fast enough around it, the Earth's surface will keep curving away from you as fast as Earth's gravity pulls you toward it. You'll keep going round and round the Earth, never getting any closer to it. This is called orbiting the Earth and the path you follow around the Earth is called an orbit. Since you don't get any closer to the Earth, it's as if the Earth is no longer pulling on you and so you have no weight — you're weightless.

The same is true if you travel fast enough around anything else in the universe. The speed you'll need depends on how bulky it is and how far away you are from it.

{Include (parts of) How does gravity change what happens elsewhere? ...?}

{Do not include any material from the So how much would I weigh on the Moon? and Astronomerese sections as it is inappropriate and/or too complicated for a Wikijunior book ...?}

{Do not include any more material on this page (with the exception of an image or two) in order to keep it succinct?}


text:
User:Chlewey

Carlos Th

Wikipedia

ca:Usuari:Chlewey da:Bruger:Chlewey de:Benutzer:Chlewey es:Usuario:Chlewey fr:Utilisateur:Chlewey it:Utente:Chlewey hu:User:Chlewey nl:Gebruiker:Chlewey ja:利用者:Chlewey pl:Wikipedysta:Chlewey pt:Usuário:Chlewey sk:Redaktor:Chlewey sv:Användare:Chlewey

title: User:Chlewey