984 resultados para Blame attribution


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Individuals seeking compensation following traumatic brain injury (TBI) are often found to report a disproportionately high level of symptoms relative to objective indicators of impairment. Previous studies highlight that level of symptom reporting is also related to self-awareness, causal attribution, and emotional wellbeing. Therefore, the reasons for high symptom reporting in the context of compensation are generally unclear. This study aimed to identify whether self-awareness, causal attribution, and emotional wellbeing are significantly associated with level of symptom reporting after controlling for compensation status. A sample of 54 participants with TBI comprised two groups, namely, claimants (n = 27) and non-claimants (n = 27), who were similar in terms of demographic and neuro-cognitive variables. Participants completed the Symptom Expectancy Checklist, Hospital Anxiety Depression Scale, Awareness Questionnaire and a causal attribution scale. A series of independent t tests and Pearson's correlations identified that a higher level of symptom reporting was associated with the following: seeking compensation, less severe TBI, increased age, greater self-awareness, increased post-injury changes reported by relatives, a higher level of mood symptoms, and a tendency to blame other people. Multivariate analysis identified that after controlling for demographic, injury, and compensation status variables, level of mood symptoms and self-awareness were significantly associated with level of symptom reporting. The findings suggest that mood symptoms and heightened self-awareness are significantly related to high symptom reporting independent of compensation status, thus supporting the need for clinicians to interpret symptom reporting within a biopsychosocial context.

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This research examines whether evaluations of positive deviates (i.e. high achieving group members) are influenced by the attributions they make for their performance. We argue that ingroup positive deviates who make group attributions help enhance the ingroup's image and thus attract favorable evaluations. In Experiment 1, ingroup positive deviates who made group attributions were generally evaluated more favorably than ingroup positive deviates who made individual attributions. There was also evidence that the positive deviates' attribution style influenced group and self-evaluations. Evaluations of outgroup positive deviates were not influenced by their attribution style. In Experiment 2, an ingroup positive deviate who was successful and attributed that success to the group was upgraded relative to an ingroup positive deviate who made individual attributions. Group evaluations were also higher when the positive deviate made group attributions. This pattern did not emerge when the positive deviate failed. The results are discussed from a social identity perspective.

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In this paper we explore the use of text-mining methods for the identification of the author of a text. We apply the support vector machine (SVM) to this problem, as it is able to cope with half a million of inputs it requires no feature selection and can process the frequency vector of all words of a text. We performed a number of experiments with texts from a German newspaper. With nearly perfect reliability the SVM was able to reject other authors and detected the target author in 60–80% of the cases. In a second experiment, we ignored nouns, verbs and adjectives and replaced them by grammatical tags and bigrams. This resulted in slightly reduced performance. Author detection with SVMs on full word forms was remarkably robust even if the author wrote about different topics.

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We undertook a secondary analysis of in-depth interviews with white (n = 32) and Pakistani and Indian (n = 32) respondents who had type 2 diabetes, which explored their perceptions and understandings of disease causation. We observed subtle, but important, differences in the ways in which these respondent groups attributed responsibility and blame for developing the disease. Whereas Pakistani and Indian respondents tended to externalise responsibility, highlighting their life circumstances in general and/or their experiences of migrating to Britain in accounting for their diabetes (or the behaviours they saw as giving rise to it), white respondents, by contrast, tended to emphasise the role of their own lifestyle 'choices' and 'personal failings'. In seeking to understand these differences, we argue for a conceptual and analytical approach which embraces both micro- (i.e. everyday) and macro- (i.e. cultural) contextual factors and experiences. In so doing, we provide a critique of social scientific studies of lay accounts/understandings of health and illness. We suggest that greater attention needs to be paid to the research encounter (that is, to who is looking at whom and in what circumstances) to understand the different kinds of contexts researchers have highlighted in presenting and interpreting their data. © 2007 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

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We report findings which suggest perception of 'higher order' attributes such as gender and social dominance are perceived from a schematic face. To investigate a large population, the first two experiments were carried out in both the traditional manner and on the Internet. Results obtained from both were not significantly different so the data sets were combined. Lowered eyebrow position was a strong indicator of both social dominance and the male gender. A schematic face with a sad mouth resulted in the face's being viewed as less dominant and less male. Eyegaze direction also was investigated and discussed in terms of dyadic influence. Evidence supported the assumption that both social dominance and the male gender are perceived through similar facial configurations on a schematic face. Limitations include the use of schematic face pairs, and the presentation of single faces in research is discussed.

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The basic assumption of quantitative authorship attribution is that the author of a text can be selected from a set of possible authors by comparing the values of textual measurements in that text to their corresponding values in each possible author's writing sample. Over the past three centuries, many types of textual measurements have been proposed, but never before have the majority of these measurements been tested on the same dataset. A large-scale comparison of textual measurements is crucial if current techniques are to be used effectively and if new and more powerful techniques are to be developed. This article presents the results of a comparison of thirty-nine different types of textual measurements commonly used in attribution studies, in order to determine which are the best indicators of authorship. Based on the results of these tests, a more accurate approach to quantitative authorship attribution is proposed, which involves the analysis of many different textual measurements.

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One routine “common sense” means of explaining sexual violence is the ideologically facilitated tendency to blame the victim, and previous research has identified patterns of victim-blaming in the talk of perpetrators of rape, and also in that of the professionals who deal with rape in their day-to-day work. This article focuses on the discursive resources drawn on in police interviews by rape victims themselves as they attempt to account for their own behaviour in relation to the attack. It identifies and describes points within interviewees’ talk where they produce “accounts” (Potter and Wetherell, 1987), and considers what these tell us about the participants’ shared understanding of what is relevant to the on-going talk. Occasions when there is evidence of a mis-match in the understanding of the participants will also be discussed. The analyses illustrate that for the accounts of interviewees to be heard as relevant, a number of prevalent and problematic themes of victim-blaming must be assumed. Interviewees anticipate and pre-empt implications that various aspects of their own behaviour contributed to their attack, and interviewers vary in the level of skill they display at negotiating these shared understandings.

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A major area of research in the realm of Industrial/Organizational Psychology is the exploration of specific job performance behaviors such as organizational citizenship behaviors (GCBs). However, there is a dearth of research examining how peers react to OCBs and the performers of such behaviors. Bolino noted that determining how people attribute motives to these OCBs is an important yet unanswered question in industrial/organizational psychology. The present study attempted to provide insight on what observer (or rater) traits affect the motives attributed to organizational citizenship behaviors. In particular, the effects of personality traits such as the Big Five personality factors, self-monitoring, individualism-collectivism, negative affectivity and identity factors such as cultural mistrust, ethnic orientation, and perceived similarity were examined. A within-subjects survey design was used to collect data on six hypothetical organizational citizenship behaviors from a sample of 369 participants. The gender and ethnicity of the individuals performing the hypothetical organizational citizenship behaviors were manipulated (i.e., male or female; African-American, Hispanic, or White). ^ Results indicated that both similarity (t(368) = 5.13; p .01) and personality factors (R2 = .06 for genuine motives and R2 = .05 for self-serving motives) had an effect on which motive (genuine or self-serving) was attributed to organizational citizenship behaviors. Support was found for an interaction between similarity and the observer's personality trait of conscientiousness when attributing genuine motives to organizational citizenship behaviors. Finally, specific organizational citizenship behaviors such as altruism were linked to genuine motives while OCBs like conscientiousness, sportsmanship, and civic virtue were associated with self-serving motives. ^