Humanizing Outgroups Through Multiple Categorization
نویسندگان
چکیده
منابع مشابه
Humanizing Outgroups Through Multiple Categorization
Do you identify with: □ sporty people □ sedentary people Do you identify with people who like: □ modern music □ classic music Do you identify with people who: □ support the local football team □ do not support the local football team Do you identify with: □ vegetarians □ not vegetarians
متن کاملChanging categorization of self can change emotions about outgroups
0022-1031/$ see front matter 2008 Elsevier Inc. A doi:10.1016/j.jesp.2008.03.014 * Corresponding author. Fax: +1 805 893 4303. E-mail address: [email protected] (D.G. Ray). Drawing on Intergroup Emotions Theory [Mackie, D. M., Maitner, A. T., & Smith, E. R. (in press). Intergroup emotions theory. In T.D. Nelson (Ed.), Handbook of Prejudice, Stereotyping, and Discrimination, New York: Erlbaum.]...
متن کاملNatural categorization through multiple feature learning in pigeons.
Recently (Troje, Huber, Loidolt, Aust, & Fieder 1999), we found that pigeons discriminated between large sets of photorealistic frontal images of human faces on the basis of sex. This ability was predominantly based on information contained in the visual texture of those images rather than in their configural properties. The pigeons could learn the distinction even when differences of shape and...
متن کاملMultiple categorization of search results
The number of publications available to physicians and patients is increasing at an alarming rate. Although users can use tools to assist in reformulating their query, this approach is ineffective when their information needs are imprecise or many documents are relevant. The ranked list presentation of documents provides little or no information relating documents to the initial query or to eac...
متن کاملWeb prefetching through automatic categorization
The present report provides a novel transparent and speculative algorithm for content based web page prefetching. The proposed algorithm relies on a user profile that is dynamically generated when the user is browsing the Internet and is updated over time. The objective is to reduce the user perceived latency by anticipating future actions. In doing so the adaboost algorithm is used in order to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Personality and Social Psychology Bulletin
سال: 2016
ISSN: 0146-1672,1552-7433
DOI: 10.1177/0146167216636624