963 research outputs found

    Selective self-categorization: Meaningful categorization and the in-group persuasion effect

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    Research stemming from self-categorization theory (Turner et al., 1987) has demonstrated that individuals are typically more persuaded by messages from their in-group than by messages from the out-group. The present research investigated the role of issue relevance in moderating these effects. In particular, it was predicted that in-groups would only be more persuasive when the dimension on which group membership was defined was meaningful or relevant to the attitude issue. In two studies, participants were presented with persuasive arguments from either an in-group source or an out-group source, where the basis of the in-group/out-group distinction was either relevant or irrelevant to the attitude issue. Participants' attitudes toward the issue were then measured. The results supported the predictions: Participants were more persuaded by in-group sources than out-group sources when the basis for defining the group was relevant to the attitude issue. However, when the defining characteristic of the group was irrelevant to the attitude issue, participants were equally persuaded by in-group and out-group sources. These results support the hypothesis that the fit between group membership and domain is an important moderator of self-categorization effects

    Study of Digital Competence of the Students and Teachers in Ukraine

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    Professional fulfillment of the personality at the conditions of the digital economy requires the high level of digital competency. One of the ways to develop these competencies is education. However, to provide the implementation of digital education at a high level, the digital competency of the teachers and students is a must. This paper presents explanations on the level determination of the digital competencies for teachers and students in Ukraine according to the DigComp recommendations. We tried to identify the main factors that reflect the degree of readiness teachers and students for digital education based on their self-evaluation. We also attempted to estimate the level of digital competencies based on the analysis of Case-Studies execution results. The complex analysis let us assess the connection between respondents’ self-evaluation and their real competencies. Here we provide a methodology and a model of level competencies determination by means of a survey, expert case rating and the results of the statistical analysis. On the basis of the obtained results, this paper suggests further research prospects and recommendations on the digital competency development in educational institutions in Ukraine

    Inner wellbeing: concept and validation of a new approach to subjective perceptions of wellbeing-India

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    © The Author(s) 2013. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This paper describes the conceptual development of a multi-domain, psychosocial model of 'Inner Wellbeing' (IWB) and assesses the construct validity of the scale designed to measure it. IWB expresses what people think and feel they are able to be and do. Drawing together scholarship in wellbeing and international development it is grounded in field research in marginalised, rural communities in the global South. Results from research in India at two points in time (2011 and 2013) are reported. At Time 1 (n = 287), we were unable to confirm an eight-factor, correlated model as distinct yet interrelated domains. However, at Time 2 (n = 335), we were able to confirm a revised, seven-factor correlated model with economic confidence, agency and participation, social connections, close relationships, physical and mental health, competence and self-worth, and values and meaning (five items per domain) as distinct yet interrelated domains. In particular, at Time 2, a seven-factor, correlated model provided a significantly better fit to the data than did a one-factor model.This work is supported by the Economic and Social Research Council/Department for International Development Joint Scheme for Research on International Development (Poverty Alleviation) grant number RES-167-25-0507 ES/H033769/1. Special thanks are due to Chaupal and Gangaram Paikra, Pritam Das, Usha Kujur, Kanti Minjh, Susanna Siddiqui, and Dinesh Tirkey

    Who I Am: The Meaning of Early Adolescents’ Most Valued Activities and Relationships, and Implications for Self-Concept Research

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    Self-concept research in early adolescence typically measures young people’s self-perceptions of competence in specific, adult-defined domains. However, studies have rarely explored young people’s own views of valued self-concept factors and their meanings. For two major self domains, the active and the social self, this mixed-methods study identified factors valued most by 526 young people from socioeconomically diverse backgrounds in Ireland (10-12 years), and explored the meanings associated with these in a stratified subsample (n = 99). Findings indicate that self-concept scales for early adolescence omit active and social self factors and meanings valued by young people, raising questions about content validity of scales in these domains. Findings also suggest scales may under-represent girls’ active and social selves; focus too much on some school-based competencies; and, in omitting intrinsically salient self domains and meanings, may focus more on contingent (extrinsic) rather than true (intrinsic) self-esteem

    Comparing Competing Theories on the Causes of Mandate Perceptions

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    The discussion of presidential mandates is as certain as a presidential election itself. Journalists inevitably discuss whether the president-elect has a popular mandate. Because they see elections as too complex to allow the public to send a unitary signal, political scientists are more skeptical of mandates. Mandates, however, have received new attention by scholars asking whether perceptions of mandate arise and lead representatives to act as if voters sent a policy directive. Two explanations have emerged to account for why elected officials might react to such perceptions. One focuses on the President’s strategic decision to declare a mandate, the second on how members of Congress read signals of changing preferences in the electorate from their own election results. We test these competing views to see which more accurately explains how members of Congress act in support of a perceived mandate. The results indicate that members respond more to messages about changing preferences than to the president’s mandate declaration

    The Toxic Effects of Cigarette Additives. Philip Morris' Project Mix Reconsidered: An Analysis of Documents Released through Litigation

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    Stanton Glantz and colleagues analyzed previously secret tobacco industry documents and peer-reviewed published results of Philip Morris' Project MIX about research on cigarette additives, and show that this research on the use of cigarette additives cannot be taken at face value

    The South, the suburbs, and the Vatican too: explaining partisan change among Catholics

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    This paper explains changes in partisanship among Catholics in the last quarter of the 20th Century using a theory of partisan change centered on the contexts in which Catholics lived. Catholics were part of the post-New Deal Democratic coalition, but they have become a swing demographic group. We argue that these changes in partisanship are best explained by changes in elite messages that are filtered through an individual’s social network. Those Catholics who lived or moved into the increasingly Republican suburbs and South were the Catholics who were most likely to adopt a non-Democratic partisan identity. Changes in context better explain Catholic partisanship than party abortion policy post Roe v. Wade or ideological sorting. We demonstrate evidence in support of our argument using the ANES cumulative file from 1972 through 2000

    Overestimating Outcome Rates: Statistical Estimation When Reliability Is Suboptimal

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    To demonstrate how failure to account for measurement error in an outcome (dependent) variable can lead to significant estimation errors and to illustrate ways to recognize and avoid these errors. Data Sources . Medical literature and simulation models. Study Design/Data Collection . Systematic review of the published and unpublished epidemiological literature on the rate of preventable hospital deaths and statistical simulation of potential estimation errors based on data from these studies. Principal Findings . Most estimates of the rate of preventable deaths in U.S. hospitals rely upon classifying cases using one to three physician reviewers (implicit review). Because this method has low to moderate reliability, estimates based on statistical methods that do not account for error in the measurement of a “preventable death” can result in significant overestimation. For example, relying on a majority rule rating with three reviewers per case (reliability ∼0.45 for the average of three reviewers) can result in a 50–100 percent overestimation compared with an estimate based upon a reliably measured outcome (e.g., by using 50 reviewers per case). However, there are statistical methods that account for measurement error that can produce much more accurate estimates of outcome rates without requiring a large number of measurements per case. Conclusion . The statistical principles discussed in this case study are critically important whenever one seeks to estimate the proportion of cases belonging to specific categories (such as estimating how many patients have inadequate blood pressure control or identifying high-cost or low-quality physicians). When the true outcome rate is low (<20 percent), using an outcome measure that has low-to-moderate reliability will generally result in substantially overestimating the proportion of the population having the outcome unless statistical methods that adjust for measurement error are used.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74896/1/j.1475-6773.2006.00661.x.pd
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