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Найдены 73 публикации
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Статья
Medushevsky A. N. Forensic Research & Criminology International Journal. 2018. Vol. 6. No. 5. P. 361-363.
Добавлено: 8 января 2019
Статья
Bobrovnikov V. Insight Turkey. 2018. Vol. 20. No. 4. P. 249-270.
Добавлено: 10 февраля 2019
Статья
Sabucedo J. M., Dono M., Grigoryev D. et al. Plos One. 2019. Vol. 14. No. 6. P. 1-17.

Current predictive models of collective action have devoted little attention to personal values, such as morals or ideology. The present research addresses this issue by incorporating a new axiological path in a novel predictive model of collective action, named AICAM. The axiological path is formed by two constructs: ideology and moral obligation. The model has been tested for real normative participation (Study 1) and intentional non-normative participation (Study 2). The sample for Study 1 included 531 randomly selected demonstrators and non-demonstrators at the time of a protest that took place in Madrid, May 2017. Study 2 comprised 607 randomly selected participants who filled out an online questionnaire. Structural equation modelling analysis was performed in order to examine the fit and predictive power of the model. Results show that the model is a good fit in both studies. It has also been observed that the new model entails a significant addition of overall effect size when compared with alternative models, including SIMCA. The present research contributes to the literature of collective action by unearthing a new, independent path towards collective action that is nonetheless compatible with previous motives. Implications for future research are discussed, mainly stressing the need to include moral and ideological motives in the study of collective action engagement.  

Добавлено: 1 июня 2019
Статья
Luna K., Albuquerque P. B., Martín-Luengo B. Memory and Cognition. 2019. Vol. 47. No. 1. P. 106-116.

Items presented in large font are rated with higher judgments of learning (JOLs) than those presented in small font. According to current explanations of this phenomenon in terms of processing fluency or implicit beliefs, this effect should be present no matter the type of material under study. However, we hypothesized that the linguistic cues present in sentences may prevent using font size as a cue for JOLs. Experiment 1, with short sentences, showed the standard font-size effect on JOLs, and Experiment 2, with pairs of longer sentences, showed a reduced effect. These results suggest that linguistic factors do not prevent font size from being used for JOLs. However, Experiment 3, with both short and long sentences, showed an effect of font size only for the former and not the latter condition, suggesting that the greater amount of to-be-remembered information eliminated the font-size effect. In Experiment 4, we tested a mechanism to explain this result and manipulated cognitive load using the dot-memory task. The short sentences from Experiments 1 and 3 were used, and the results replicated the font-size effect only in the low-cognitive load condition. Our results are consistent with the idea that perceptual information is used to make JOLs only with materials such as words, word pairs, or short sentences, and that the increased cognitive load required to process longer sentences prevents using font size as a cue for JOLs.

Добавлено: 31 августа 2018
Статья
Kotusev S. International Journal of Cooperative Information Systems. 2017. Vol. 26. No. 3. P. 1-36.
Добавлено: 18 октября 2019
Статья
Kotusev S. International Journal of Enterprise Information Systems. 2017. Vol. 13. No. 2. P. 50-62.
Добавлено: 18 октября 2019
Статья
Grigoryev D., van de Vijver F., Batkhina A. Journal of Intercultural Communication Research. 2018. Vol. 47. No. 6. P. 491-509.
Добавлено: 18 июля 2018
Статья
Kotusev S. Journal of Information Technology. 2019. Vol. 34. No. 2. P. 102-128.
Добавлено: 18 октября 2019
Статья
Kotusev S. Pacific Asia Journal of the Association for Information Systems. 2018. Vol. 10. No. 4. P. 1-36.
Добавлено: 18 октября 2019
Статья
Kotusev S. International Journal of Cooperative Information Systems. 2017. Vol. 26. No. 4. P. 1-84.
Добавлено: 18 октября 2019
Статья
Kravchenko Z., Moskvina Anastasiya. Voluntas: International Journal of Voluntary and Nonprofit Organizations. 2018. Vol. 29. No. 5. P. 962-975.
Добавлено: 11 октября 2018
Статья
Goodwin D., Mapp F., Sautkina E. et al. Health and Place. 2014. Vol. 30. P. 120-126.
Добавлено: 4 октября 2018
Статья
Sarieva I. Psychology. Journal of the Higher School of Economics. 2018. Vol. 15. No. 3. P. 477-490.

Целью данного исследования была разработка и апробация шкалы, измеряющей три компонента политической самоэффективности: личную, коллективную и внешнюю самоэффективность. 12 утверждений были сформулированы на основе 4 способностей: 1) способность влиять на принятие новых законов и политических решений, 2) способность способствовать избранию политического лидера, 3) способность требовать исполнения существующих законов и политических решений и 4) способность свободно и публично выражать любые политические взгляды. Ответы респондентов российской, казахстанской и украинской выборок (N = 2184) были собраны онлайн через социальные сети в 2015-2017 годах. Структурная валидность шкалы была проанализирована с помощью конфирматорного факторного анализа. Его результаты показали, что с рядом модификаций укороченная версия предложенной модели демонстрирует хорошие показатели соответствия по всем трем выборкам. Также была успешно протестирована конфигурационная, метрическая и скалярная инвариативность укороченной версии Модели Воспринимаемой Политической Самоэффективности. Кроме того, были выявлены различия в показателях политической самоэффективности между возрастными группами и странами. В частности, люди в возрастной группе старше 30 лет демонстрировали более высокую политическую самоэффективность, чем респонденты в группе 18-19 лет. Украинские респонденты демонстрировали значительно более высокую личную и коллективную самоэффективность по сравнению с российскими и казахстанскими респондентами. Наконец, казахстанские респонденты продемонстрировали наивысший уровень внешней политической самоэффективности.

Добавлено: 14 октября 2018
Статья
Kearns A., McKee M., Sautkina E. et al. Cities. 2013. Vol. 35. P. 397-408.
Добавлено: 4 октября 2018
Статья
Berry J. W., Galyapina V. N., Lebedeva N. et al. Psychology. Journal of the Higher School of Economics. 2019. Vol. 16. No. 2. P. 232-249.
Добавлено: 24 августа 2019
Статья
Sautkina E., Goodwin D., Jones A. et al. Health and Place. 2014. Vol. 29. P. 60-66.
Добавлено: 4 октября 2018
Статья
Grigoryev D., Fiske S. T., Batkhina A. Frontiers in Psychology. 2019. Vol. 10. No. 1643. P. 1-21.

The stereotype content model (SCM), originating in the United States and generalized across nearly 50 countries, has yet to address ethnic relations in one of the world’s most influential nations. Russia and the United States are somewhat alike (large, powerful, immigrant-receiving), but differ in other ways relevant to intergroup images (culture, religions, ideology, and history). Russian ethnic stereotypes are understudied, but significant for theoretical breadth and practical politics. This research tested the SCM on ethnic stereotypes in a Russian sample (N = 1115). Study 1 (N = 438) produced an SCM map of the sixty most numerous domestic ethnic groups (both ethnic minorities and immigrants). Four clusters occupied the SCM warmth-by-competence space. Study 2 (N = 677) compared approaches to ethnic stereotypes in terms of status and competition, cultural distance, perceived region, and four intergroup threats. Using the same Study 1 groups, the Russian SCM map showed correlated warmth and competence, with few ambivalent stereotypes. As the SCM predicts, status predicted competence, and competition negatively predicted warmth. Beyond the SCM, status and property threat both were robust antecedents for both competence and warmth for all groups. Besides competition, cultural distance also negatively predicted warmth for all groups. The role of the other antecedents, as expected, varied from group to group. To examine relative impact, a network analysis demonstrated that status, competition, and property threat centrally influence many other variables in the networks. The SCM, along with antecedents from other models, describes Russian ethnic-group images. This research contributes: (1) a comparison of established approaches to ethnic stereotypes (from acculturation and intergroup relations) showing the stability of the main SCM predictions; (2) network structures of the multivariate dependencies of the considered variables; (3) systematically cataloged images of ethnic groups in Russia for further comparisons, illuminating the Russian historical, societal, and interethnic context.

Добавлено: 28 июня 2019
Статья
Sautkina E., Bond L., Kearns A. Housing Studies. 2012. Vol. 27. No. 6. P. 748-782.
Добавлено: 4 октября 2018
Статья
Kearns A., McKee M., Sautkina E. et al. Cityscape. 2013. Vol. 15. No. 2. P. 47-67.
Добавлено: 4 октября 2018
Статья
Sautkina E., Cummins S., Petticrew M. et al. Journal of Epidemiology and Community Health. 2013. Vol. 67. No. 1. P. A31-A31.
Добавлено: 4 октября 2018
Статья
Sautkina E., Kochetkov N. Bulletin of People-Environment Studies. 2008. Vol. 34. P. 35-39.
Добавлено: 12 марта 2019