The greater power of bad events over good ones is found in everyday events, major life events (e.g., trauma), close relationship outcomes, social network patterns, interpersonal interactions, and learning processes. Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones. Various explanations such as diagnosticity and salience help explain some findings, but the greater power of bad events is still found when such variables are controlled. Hardly any exceptions (indicating greater power of good) can be found. Taken together, these findings suggest that bad is stronger than good, as a general principle across a broad range of psychological phenomena.
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In Teaching History for the Common Good, Barton and Levstik present a clear overview of competing ideas among educators, historians, politicians, and the public about the nature and purpose of teaching history, and they evaluate these debates in light of current research on students' historical thinking. In many cases, disagreements about what should be taught to the nation's children and how it should be presented reflect fundamental differences that will not easily be resolved. A central premise of this book, though, is that systematic theory and research can play an important role in such debates by providing evidence of how students think, how their ideas interact with the information they encounter both in school and out, and how these ideas differ across contexts. Such evidence is needed as an alternative to the untested assumptions that plague so many discussions of history education. The authors review research on students' historical thinking and set it in the theoretical context of mediated action--an approach that calls attention to the concrete actions that people undertake, the human agents responsible for such actions, the cultural tools that aid and constrain them, their purposes, and their social contexts. They explain how this theory allows educators to address the breadth of practices, settings, purposes, and tools that influence students' developing understanding of the past, as well as how it provides an alternative to the academic discipline of history as a way of making decisions about teaching and learning the subject in schools. Beyond simply describing the factors that influence students' thinking, Barton and Levstik evaluate their implications for historical understanding and civic engagement. They base these evaluations not on the disciplinary study of history, but on the purpose of social education--preparing students for participation in a pluralist democracy. Their ultimate concern is how history can help citizens engage in collaboration toward the common good. In Teaching History for the Common Good, Barton and Levstik: *discuss the contribution of theory and research, explain the theory of mediated action and how it guides their analysis, and describe research on children's (and adults') knowledge of and interest in history; *lay out a vision of pluralist, participatory democracy and its relationship to the humanistic study of history as a basis for evaluating the perspectives on the past that influence students' learning; *explore four principal "stances" toward history (identification, analysis, moral response, and exhibition), review research on the extent to which children and adolescents understand and accept each of these, and examine how the stances might contribute to--or detract from--participation in a pluralist democracy; *address six of the principal "tools" of history (narrative structure, stories of individual achievement and motivation, national narratives, inquiry, empathy as perspective-taking, and empathy as caring); and *review research and conventional wisdom on teachers' knowledge and practice, and argue that for teachers to embrace investigative, multi-perspectival approaches to history they need more than knowledge of content and pedagogy, they need a guiding purpose that can be fulfilled only by these approaches--and preparation for participatory democracy provides such purpose. Teaching History for the Common Good is essential reading for history and social studies professionals, researchers, teacher educators, and students, as well as for policymakers, parents, and members of the general public who are interested in history education or in students' thinking and learning about the subject.
In The Righteous Mind, psychologist Jonathan Haidt answers some of the most compelling questions about human relationships: Why can it sometimes feel as though half the population is living in a different moral universe? Why do ideas such as 'fairness' and 'freedom' mean such different things to different people? Why is it so hard to see things from another viewpoint? Why do we come to blows over politics and religion? Jonathan Haidt reveals that we often find it hard to get along because our minds are hardwired to be moralistic, judgemental and self-righteous. He explores how morality evolved to enable us to form communities, and how moral values are not just about justice and equality - for some people authority, sanctity or loyalty matter more. Morality binds and blinds, but, using his own research, Haidt proves it is possible to liberate ourselves from the disputes that divide good people. A landmark contribution to humanity's understanding of itself. (The New York Times). A truly seminal book. (David Goodhart, Prospect). A tour de force - brave, brilliant, and eloquent. It will challenge the way you think about liberals and conservatives, atheism and religion, good and evil. (Paul Bloom, author of How Pleasure Works). Compelling ...a fluid combination of erudition and entertainment. (Ian Birrell, Observer). Lucid and thought-provoking ...deserves to be widely read. (Jenni Russell, Sunday Times). Jonathan Haidt is a social and cultural psychologist. He has been on the faculty of the University of Virginia since 1995 and is currently a visiting professor of business ethics at New York University's Stern School of Business. He is the co-editor of Flourishing: Positive Psychology and the Life Well Lived, and is the author of The Happiness Hypothesis: Finding Modern Truth in Ancient Wisdom.
Can hardened criminals really reform? Making Good provides resounding proof that the answer is yes. This book provides a fascinating narrative analysis of the lives of repeat offenders who, by all statistical measures, should have continued on the criminal path but instead have created lives of productivity and purpose. This examination of the phenomenology of good includes an encyclopedic review of the literature on personal reform as well as a practical guide to the use of narratives in offender counseling and rehabilitation.The author's research shows that criminals who desist from crime have constructed powerful narratives that aided them in making sense of their pasts, finding fulfillment in productive behaviors, and feeling in control of their future. Borrowing from the field of narrative psychology, Maruna argues that to truly understand offenders, we must understand the stories that they tell - and that in turn this story-making process has the capacity to transform lives. Making Good challenges some of the cherished assumptions of various therapy models for offenders and supports new paradigms for offender rehabilitation. This groundbreaking book is a must read for criminologists, forensic psychologists, lawyers, rehabilitation counselors, or anyone interested in the generative process of change.
This article reports the findings of AI4People, an Atomium-EISMD initiative designed to lay the foundations for a "Good AI Society". We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations-to assess, to develop, to incentivise, and to support good AI-which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society.
Acknowledgments. Introduction. 1. The Case for Doing at Least Some Good. 2. Corporate Social Initiatives: Six Options for Doing Good. 3. Corporate Cause Promotions: Increasing Awareness and Concern for Social Causes. 4. Cause-Related Marketing: Making Contributions to Causes Based on Product Sales. 5. Corporate Social Marketing: Supporting Behavior Change Campaigns. 6. Corporate Philanthropy: Making a Direct Contribution to a Cause. 7. Community Volunteering: Employees Donating Their Time and Talents. 8. Socially Responsible Business Practices: Discretionary Business Practices and Investments to Support Causes. 9. Twenty-five Best Practices for Doing the Most Good for the Company and the Cause. 10. A Marketing Approach to Winning Corporate Funding and Support for Social Initiatives: Ten Recommendations. Notes. Index.
What good is self-control? We incorporated a new measure of individual differences in self-control into two large investigations of a broad spectrum of behaviors. The new scale showed good internal consistency and retest reliability. Higher scores on self-control correlated with a higher grade point average, better adjustment (fewer reports of psychopathology, higher self-esteem), less binge eating and alcohol abuse, better relationships and interpersonal skills, secure attachment, and more optimal emotional responses. Tests for curvilinearity failed to indicate any drawbacks of so-called overcontrol, and the positive effects remained after controlling for social desirability. Low self-control is thus a significant risk factor for a broad range of personal and interpersonal problems.
The classic answer to what makes a decision good concerns outcomes. A good decision has high outcome benefits (it is worthwhile) and low outcome costs (it is worth it). I propose that, independent of outcomes or value from worth, people experience a regulatory fit when they use goal pursuit means that fit their regulatory orientation, and this regulatory fit increases the value of what they are doing. The following postulates of this value from fit proposal are examined: (a) People will be more inclined toward goal means that have higher regulatory fit, (b) people's motivation during goal pursuit will be stronger when regulatory fit is higher, (c) people's (prospective) feelings about a choice they might make will be more positive for a desirable choice and more negative for an undesirable choice when regulatory fit is higher, (d) people's (retrospective) evaluations of past decisions or goal pursuits will be more positive when regulatory fit was higher, and (e) people will assign higher value to an object that was chosen with higher regulatory fit. Studies testing each of these postulates support the value-from-fit proposal. How value from fit can enhance or diminish the value of goal pursuits and the quality of life itself is discussed.
No feature-based vision system can work unless good features can be identified and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world. These methods are based on a new tracking algorithm that extends previous Newton-Raphson style search methods to work under affine image transformations. We test performance with several simulations and experiments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
This paper explains the size and value “anomalies” in stock returns using an economically motivated two-beta model. We break the beta of a stock with the market portfolio into two components, one reflecting news about the market's future cash flows and one reflecting news about the market's discount rates. Intertemporal asset pricing theory suggests that the former should have a higher price of risk; thus beta, like cholesterol, comes in “bad” and “good” varieties. Empirically, we find that value stocks and small stocks have considerably higher cash-flow betas than growth stocks and large stocks, and this can explain their higher average returns. The poor performance of the capital asset pricing model (CAPM) since 1963 is explained by the fact that growth stocks and high-past-beta stocks have predominantly good betas with low risk prices.
The research on formative assessment and feedback is reinterpreted to show how these processes can help students take control of their own learning, i.e. become self‐regulated learners. This reformulation is used to identify seven principles of good feedback practice that support self‐regulation. A key argument is that students are already assessing their own work and generating their own feedback, and that higher education should build on this ability. The research underpinning each feedback principle is presented, and some examples of easy‐to‐implement feedback strategies are briefly described. This shift in focus, whereby students are seen as having a proactive rather than a reactive role in generating and using feedback, has profound implications for the way in which teachers organise assessments and support learning.
It is widely known that when there are errors with a moving-average root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We consider a class of Modified Information Criteria (MIC) with a penalty factor that is sample dependent. It takes into account the fact that the bias in the sum of the autoregressive coefficients is highly dependent on k and adapts to the type of deterministic components present. We use a local asymptotic framework in which the moving-average root is local to −1 to document how the MIC performs better in selecting appropriate values of k. In Monte-Carlo experiments, the MIC is found to yield huge size improvements to the DFGLS and the feasible point optimal PT test developed in Elliott, Rothenberg, and Stock (1996). We also extend the M tests developed in Perron and Ng (1996) to allow for GLS detrending of the data. The MIC along with GLS detrended data yield a set of tests with desirable size and power properties.
A person&apos;s physical appearance, along with his sexual identity, is the personal characteristic that is most obvious and accessible to others in social inter-action. The present experiment was designed to determine whether physically attractive stimulus persons, both male and female, are (a) assumed to possess more socially desirable personality traits than physically unattractive stimulus persons and (6) expected to lead better lives (e.g., be more competent husbands and wives, be more successful occupationally, etc.) than unattrac-tive stimulus persons. Sex of Subject X Sex of Stimulus Person interactions along these dimensions also were investigated. The present results indicate a &quot;what is beautiful is good &quot; stereotype along the physical attractiveness dimen-sion with no Sex of Judge X Sex of Stimulus interaction. The implications of such a stereotype on self-concept development and the course of social inter-action are discussed. A person&apos;s physical appearance, along with his sexual identity, is the personal character-
Consider the ridge estimate (λ) for β in the model unknown, (λ) = (X T X + nλI)−1 X T y. We study the method of generalized cross-validation (GCV) for choosing a good value for λ from the data. The estimate is the minimizer of V(λ) given by where A(λ) = X(X T X + nλI)−1 X T . This estimate is a rotation-invariant version of Allen's PRESS, or ordinary cross-validation. This estimate behaves like a risk improvement estimator, but does not require an estimate of σ2, so can be used when n − p is small, or even if p ≥ 2 n in certain cases. The GCV method can also be used in subset selection and singular value truncation methods for regression, and even to choose from among mixtures of these methods.
We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay-Neal (1995)) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The decoding of both codes can be tackled with a practical sum-product algorithm. We prove that these codes are "very good", in that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit. This result holds not only for the binary-symmetric channel but also for any channel with symmetric stationary ergodic noise. We give experimental results for binary-symmetric channels and Gaussian channels demonstrating that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved; indeed, the performance of Gallager codes is almost as close to the Shannon limit as that of turbo codes.
Examination of nature's favorite molecules reveals a striking preference for making carbon–heteroatom bonds over carbon–carbon bonds—surely no surprise given that carbon dioxide is nature's starting material and that most reactions are performed in water. Nucleic acids, proteins, and polysaccharides are condensation polymers of small subunits stitched together by carbon–heteroatom bonds. Even the 35 or so building blocks from which these crucial molecules are made each contain, at most, six contiguous C−C bonds, except for the three aromatic amino acids. Taking our cue from nature's approach, we address here the development of a set of powerful, highly reliable, and selective reactions for the rapid synthesis of useful new compounds and combinatorial libraries through heteroatom links (C−X−C), an approach we call "click chemistry". Click chemistry is at once defined, enabled, and constrained by a handful of nearly perfect "spring-loaded" reactions. The stringent criteria for a process to earn click chemistry status are described along with examples of the molecular frameworks that are easily made using this spartan, but powerful, synthetic strategy.
Abstract This article asserts that the theory of emerging adulthood is a useful way of conceptualizing the lives of people from their late teens to their mid- to late 20s in industrialized societies. The place of emerging adulthood within the adult life course is discussed. The weaknesses of previous terms for this age period are examined, and emerging adulthood is argued to be preferable as a new term for a new phenomenon. With respect to the question of whether emerging adulthood is experienced positively or negatively by most people, it is argued that it is positive for most people but entails developmental challenges that may be difficult and there is great heterogeneity, with some emerging adults experiencing serious problems. With respect to the question of whether or not emerging adulthood is good for society, it is argued that claims of the dangers of emerging adulthood are overblown, but emerging adulthood is probably a mixed blessing for society.
Survey research is sometimes regarded as an easy research approach. However, as with any other research approach and method, it is easy to conduct a survey of poor quality rather than one of high quality and real value. This paper provides a checklist of good practice in the conduct and reporting of survey research. Its purpose is to assist the novice researcher to produce survey work to a high standard, meaning a standard at which the results will be regarded as credible. The paper first provides an overview of the approach and then guides the reader step-by-step through the processes of data collection, data analysis, and reporting. It is not intended to provide a manual of how to conduct a survey, but rather to identify common pitfalls and oversights to be avoided by researchers if their work is to be valid and credible.
Answers to commonly asked questions about how good-to-great principles can help social sector organizations make the leap to greatness, using interviews with over 100 social sector leaders.