The Behavioral Development Bulletin最新文献

{"title":"Stages of Investing Generated Using the Model of Hierarchical Complexity","authors":"M. Commons, Christine Spencer Thexton","doi":"10.1037/H0101032","DOIUrl":"https://doi.org/10.1037/H0101032","url":null,"abstract":"Stage 10 As developmental stage increases, individuals possess the skills, knowledge, and understanding of the lower stages, as well as a new set of skills, knowledge, and understanding that allow the jump to the higher stage. At the Abstract Stage 10, the decision-making process on investment strategy is heavily influenced by outside sources. A person at the Abstract Stage follows the crowd as they buy low and sell high because that is what others are doing. They listen to others to find a “highly rated” investment advisor and then do what their advisor says no matter what the performance. This directly leads to large fees, low returns, and a high likelihood of losing money. They do not yet understand ratios and percentages in the context of interest rates and percent fees on mutual funds, nor do they understand percent inflation and why the return on bonds may not keep up with inflation. The “Wealth Effect” (Darby, 1987; Jelveh, 2008; Zubin, 2008) is an economic term where an increase in perceived or actual wealth leads to an increase in spending, or vice versa with a perceived or actual decrease in wealth. Temporary wealth changes have a smaller effect on consumption changes than permanent wealth changes. With the wealth effect people psychologically associate higher net worth with having more disposable income. This is evident at Abstract Stage 9 where big gains in portfolio values attributable to bull markets make people feel secure about their wealth, so they spend more of it. At this stage, people tend to invest more at the height of markets and overconfidence, caused by the wealth effect, leads to bigger losses when the market crashes. People also pull money out at the bottom of the market. They make overcorrections that are similar to those made by novice sailors. If one tries to turn too quickly, one will find that most times one ends up turning too far across the wind. One’s instinctive reaction is to turn back the other direction, most times ending up head to the wind instead. The process of overcorrecting, both in investing and on the water, is the result of riskaversion. This leads to smaller overall gains when the markets go backup. If the wealth effect is too strong, meaning people overcorrect for changes in the markets by selling too much when the prices are low and buying too much when the prices are high.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127110584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Directions Toward a Meta-Process Model of Decision Making: Cognitive and Behavioral Models of Change","authors":"Joseph P. McFall","doi":"10.1037/H0101038","DOIUrl":"https://doi.org/10.1037/H0101038","url":null,"abstract":"Hundreds of partially unique decision-making models, primarily differing by context, currently coexist in the decision-making literature. Yet we have 1 brain that makes decisions in all these contexts. The study of decision making needs integrative metatheory to advance and test the research questions of tomorrow. Existing descriptive, behavioral, information processing, dual process, fuzzy trace, and motivational and contextual models are examined to find commonalities that may inform future attempts at building a holistic, dynamic, integrative metatheoretical model of everyday decision making. Features of such a future metamodel are described and related to the study of behavioral development, such as the value of reinforcement as a mechanism of change.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116752959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Replacing Maslow’s needs hierarchy with an account based on stage and value.","authors":"W. Harrigan, M. Commons","doi":"10.1037/H0101036","DOIUrl":"https://doi.org/10.1037/H0101036","url":null,"abstract":"Maslow’s needs hierarchy consisted of a set of mentalistic inferences. The new account takes the same situations that Maslow accounts for while using behavioral metrics. This model of value and stage is applied to Maslow’s needs hierarchy model. Needs may be understood as primary and secondary reinforcers that change with stage. Primary reinforcers are biologically built-in, such as food, sleep, and social stimuli. Secondary reinforcers are learned when paired with a primary reinforcer. For example, money is a powerful reinforcer when paired with things it can purchase. Secondary reinforcers are stimuli that have conditioned become reinforcing by pairing with a previously reinforcing stimulus. As one moves up in stage, secondary reinforcers become more complex. Individuals who understand complex contingencies may be more likely to act on long term benefits. An example of a secondary reinforcer is money. Individuals who score higher on Maslow’s hierarchy should also show higher stage social perspective taking skill.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129470296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stage of Development and Million Dollar per Year Earning From Sales","authors":"E. A. Goodheart, M. Commons, S. Chen","doi":"10.1037/H0101040","DOIUrl":"https://doi.org/10.1037/H0101040","url":null,"abstract":"This article presents cases showing that people with higher stages in the Model of Hierarchical Complexity can handle more complicated job responsibilities. Account Executives and Consultants from a training company participated in the study. According to the Hierarchical Complexity Scoring System (HCSS; Commons, Miller, Goodheart, & Danaher-Gilpin, 2005) participants’ person scores are based on the highest stage item the participant performed in the interview. Six of 9 Accountant Executives and 4 of 15 Consultants performed at the Metasystematic Stage 13. The study indicated that people who perform at the Metasystematic Stage 13 will have a better chance of achieving higher compensation than people performing at the Formal Stage 11 or Systematic Stage 12.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stage of pricing strategy predicts earnings: A study of informal economics.","authors":"P. Miller, M. Commons, Eva Yujia Li, Hudson F Golino, Lucas Alexander Haley Commons-Miller, Charu T. Tuladhar","doi":"10.1037/H0101031","DOIUrl":"https://doi.org/10.1037/H0101031","url":null,"abstract":"An individual’s income results from the way or ways in which they work and how they are paid. In recent years, income disparities have been rising in a number of countries (e.g., Piketty & Saez, 2003). A common notion is that income disparity can be reduced by creating equal opportunity for education for all individuals. To put this idea to the test, we examined the relative contributions of education, of country of origin, and of stage of development to people’s income. Specifically, the stage of pricing strategies used and the level of education were used to predict income. Participants were individuals who worked in the informal economies within 2 countries: Brazil and the United States. Two groups of people were studied: people who sell things on the sidewalks or at flea markets (peddlers) and people who transport goods (carters). All participants were asked how they set their prices, and how much money they earned either per day, per week or per month. A regression analysis showed that behavioral stage of an individual’s pricing strategy and their country of origin were the best predictors of income obtained, R(44) 0.705, (R .497; F(1, 44) 20.78, p .0005). Stage and country both contributed significantly to the income obtained; for stage, 0.408, and for country, .501. A second regression analysis that included education found that education did not significantly predict earnings, over and above stage and country of origin. These results indicate that education by itself may not be enough to increase earnings and decrease income disparities. Unless there are interventions to raise individuals’ developmental stage social stratification will likely continue to exist and even to increase.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128768862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Interaction Between Stage and Value","authors":"M. Commons","doi":"10.1037/H0101037","DOIUrl":"https://doi.org/10.1037/H0101037","url":null,"abstract":"This issue is about a behavioral-developmental account of stage, value, and action that integrates the following three paradigms: (a) a behavioral paradigm, which includes notions of value (as established by reinforcement); (b) a developmental paradigm, as primarily measured by stage of development; and, in some cases, (c) a quantitative paradigm. A mathematical technique for predicting an organism’s behavior that is based on the integration of these different paradigms would be extremely valuable and widely applicable to a range of organisms and behaviors, as discussed in the various contributions to the issue. This issue presents the first examples of a general and more integrative theory of behavior based on this approach. In this introduction, the interplay of stage of performance and the valuation of reinforcers in predicting behavior or action are examined. This is done to provide some additional background on the issues involved. To reasonably predict behavior, one must consider (a) the stage of development, measured here in terms of the hierarchical complexity of tasks successfully completed, and (b) the value of outcomes of behavior, operationalized either as the overall value obtained, the value that is discounted due to delay, and perceived value under conditions of risk.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133758016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Order of Hierarchical Complexity (\"Stage\") of Items Used to Measure Forensic Experts' Perceptions of Expert Bias Predicts the Amount of Bias","authors":"M. Commons","doi":"10.1037/H0101035","DOIUrl":"https://doi.org/10.1037/H0101035","url":null,"abstract":"This article will show that developmental stage will account for the biasing value of items used to test expert witness bias. Bias is usually thought of as a dependent variable to be described and predicted. In the simplest sense, bias represents a deviation from having a neutral value ascribed to a choice. It therefore represents value. In psychology and economics it is a choice-outcome–related dependent variable that alters the rating or probability of an action. Hence it belongs to the Behavioral Economics “value/ reinforcement” paradigm. In behavioral economics, all bias reflects the probability of making a response (or the tendency to make a response) based on perceived value of the outcome. The more often one does something that has a positive outcome, the higher the value of doing it. This is true whether an expert is aware of this effect or not. Stage of development is usually thought of as also a dependent variable, but here it will be used as an independent variable to predict bias.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134202362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in the model of hierarchical complexity (MHC)","authors":"M. Commons, S. Chen","doi":"10.1037/H0101080","DOIUrl":"https://doi.org/10.1037/H0101080","url":null,"abstract":"The model of hierarchical complexity (MHC) has a long history that only in very recent years resulted in its formal specification as a general model. A brief history of the origins of the notion of hierarchical complexity follows. This is done in order to identify what the steps were and also those who played key roles in the model’s development over these many years. In tracing the evolution of the MHC, there are four periods, each involving different people. The two earliest periods were Commons’ pre-college years, college and graduate school years, followed by a period of more active and direct development from 1973 to 1982. After the model was developed, there were advances in the period from 1982 to present.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Goal pursuit and eudaimonic well-being among university students: Metacognition as the mediator","authors":"Yalda Amir Kiaei, T. Reio","doi":"10.1037/H0101085","DOIUrl":"https://doi.org/10.1037/H0101085","url":null,"abstract":"This study investigated the relationship between goal-striving, goal-aspiration, metacognition, and eudaimonic wellbeing (EWB). Inspired by Aristotle’s teaching, the rationale for this study is that eudaimonic well-being is achievable through self-actualizing processes such as goal-striving and goal-aspiration and by exercise of reason. Goal-striving, metacognition (as a way of exercise of reason), and goal-aspiration (as an indicator of eudaimonic pursuits) were explored in relation to EWB. A mediation analysis of a sample of 513 university students (Mage = 25.07, SD = 7.21) indicated that metacognition partially mediated the relationship between goal-striving and EWB for the full sample (p < .001) and goal-aspiration moderated this relationship. High goal-aspiration indicated a full mediation while low goal-aspiration indicated only a partial mediation. The finding suggests that metacognition which is a teachable competence and goal-aspiration which is a trainable desire can play a determining role in individuals’ selfactualization and EWB.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127124320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model of stage change explains the average rate of stage of development and its relationship to the predicted average stage (\"smarts\")","authors":"M. Commons, L. S. Miller, Sagun Giri","doi":"10.1037/H0101076","DOIUrl":"https://doi.org/10.1037/H0101076","url":null,"abstract":"A number of different previous methods for measuring “smarts” have led to the model of hierarchical complexity (MHC), a context free neo-Piagetian mathematical model of behavioral complexity. It provides a way to classify tasks as to their hierarchical complexity. Using the model of hierarchical complexity, this study examines how differences in rate of stage change results in a difference in the highest average stage (smarts”) attained by 70 year old adults. The average stage of development (“smarts”) was shown to be predicted by the log of age with an r = .79. It uses data from Colby, Kohlberg, Gibbs, Lieberman (1983) to test the model. It also predicts that on the average there is one stage of development during adulthood.","PeriodicalId":314223,"journal":{"name":"The Behavioral Development Bulletin","volume":"195 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120979001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}