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Journal articles on the topic 'Self-categorization'

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Published: 4 June 2021

Last updated: 29 January 2023

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1

Rhee, Eunice Yunjin. "Strategic Categorization: Vertical and Horizontal Changes in Self- Categorization." Academy of Management Proceedings 2015, no. 1 (January 2015): 10986. http://dx.doi.org/10.5465/ambpp.2015.165.

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2

Leonardelli, Geoffrey J., and Soo Min Toh. "Social Categorization in Intergroup Contexts: Three Kinds of Self-Categorization." Social and Personality Psychology Compass 9, no. 2 (February 2015): 69–87. http://dx.doi.org/10.1111/spc3.12150.

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3

Wyer, Natalie A. "Selective Self-Categorization: Meaningful Categorization and the In-Group Persuasion Effect." Journal of Social Psychology 150, no. 5 (September 16, 2010): 452–70. http://dx.doi.org/10.1080/00224540903365521.

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4

Oldmeadow, Julian A., Michael J. Platow, Margaret Foddy, and Donna Anderson. "Self-Categorization, Status, and Social Influence." Social Psychology Quarterly 66, no. 2 (June 2003): 138. http://dx.doi.org/10.2307/1519844.

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5

Chalk, Holly McCartney. "Disability Self-Categorization in Emerging Adults." Emerging Adulthood 4, no. 3 (May 7, 2015): 200–206. http://dx.doi.org/10.1177/2167696815584540.

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6

Athenstaedt, Ursula, Cornelia Heinzle, and Gudrun Lerchbaumer. "Gender Subgroup Self-Categorization and Gender Role Self-Concept." Sex Roles 58, no. 3-4 (October 26, 2007): 266–78. http://dx.doi.org/10.1007/s11199-007-9288-z.

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7

Totaro, Paolo, and Thais Alves Marinho. "The duality of social self-categorization in consumption." Journal of Consumer Culture 19, no. 2 (July 6, 2017): 189–212. http://dx.doi.org/10.1177/1469540517717774.

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“Consumer culture” theories frequently claim that people use symbols of consumption to socially self-categorize and satisfy their needs for assimilation or differentiation. Through two empirical quantitative studies, we argue that self-categorization operates according to a duality overlooked by these theories. On one hand, self-categorization can be understood as the assimilation of the “I” into a normatively well-characterized group, a self-categorization that we define as “ontological” in this article. On the other hand, it can be understood as the identification with socially standardized and impersonal models, a self-categorization that we term “formal.” In the two studies, we investigated whether the psychologically perceived distance between the in-group and out-group (metacontrast) is greater in ontological than in formal self-categorization and, second, whether these two forms of self-categorizations operate independently (not correlated) in consumption. The results support the two hypotheses. However, further studies should be developed in order to give a more definitive character to the theory. If the findings of this work were to be confirmed by other ecological contexts and sampling techniques, there might be consequences for “self-brand connection” analyses and in general for consumption studies where social self-categorization theory can be applied.

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8

Peterson, Jordan B., Erin Driver-Linn, and Colin G. DeYoung. "Self-deception and impaired categorization of anomaly." Personality and Individual Differences 33, no. 2 (July 2002): 327–40. http://dx.doi.org/10.1016/s0191-8869(01)00158-1.

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9

Abrams, Dominic, and Michael A. Hogg. "Social Identification, Self-Categorization and Social Influence." European Review of Social Psychology 1, no. 1 (January 1990): 195–228. http://dx.doi.org/10.1080/14792779108401862.

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10

Mosqueira, F. G. "A categorization of prebiotic self-reproducible systems." Origins of Life and Evolution of the Biosphere 26, no. 3-5 (October 1996): 427–28. http://dx.doi.org/10.1007/bf02459850.

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11

Simon, Bernd, Claudia Hastedt, and Birgit Aufderheide. "When self-categorization makes sense: The role of meaningful social categorization in minority and majority members' self-perception." Journal of Personality and Social Psychology 73, no. 2 (August 1997): 310–20. http://dx.doi.org/10.1037/0022-3514.73.2.310.

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12

Park, Seongjin, Namkyeong Jang, and Yukyoum Kim. "Categorization Effect on Exercise Goal Progress Perception and Motivation: Moderating the Role of Self-efficacy." Korean Journal of Sport Science 33, no. 4 (December 31, 2022): 624–35. http://dx.doi.org/10.24985/kjss.2022.33.4.624.

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PURPOSE This research explores the underlying mechanism that determines how people perceive their goal progress and its relation with their motivation and self-efficacy. METHODS Three hundred and sixty Koreans who participated in an online survey were given salient individual exercise goals (11 workouts), and they reported their self-efficacy, goal progress perception, and motivation. We conducted dummy variable multiple regression analysis (2 [absolute progress-low (27%) vs. high (73%)] X 2 [categorization vs. no-categorization]) and multiple moderated mediation analysis based on Process Model 7 and 21 (Hayes, 2017). RESULTS The findings showed significant interaction between categorization and absolute progress on progress perception. In low progress condition, the categorization group perceived more progress than no categorization group and contrary effect in high progress condition. For motivation, in low progress condition, categorization group was more motivated than no categorization group, and inverse effect in high progress condition. Moreover, there was no direct effect, but only low self-efficacy group played the moderating role between perceived progress and motivation in conditional indirect effect. Lastly, the result indicated significant multiple moderated mediation effect. CONCLUSIONS This research theoretically contributes to the domains of categorization and motivation. Sport marketers can utilize categorization as a strategy by breaking down yearly memberships into monthly categories based on consumers perceptions. Future research can include subsequent motivation after a superordinate goal is completed.

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13

Grossberg, Stephen. "Self-organizing features and categories through attentive resonance." Behavioral and Brain Sciences 21, no. 1 (February 1998): 27–28. http://dx.doi.org/10.1017/s0140525x98360100.

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Because “people create features to subserve the representation and categorization of objects” (abstract) Schyns et al. “provide an account of feature learning in which the components of a representation have close ties to the categorization history of the organism” (sect. 1.1). This commentary surveys self-organizing neural models that clarify this process. These models suggest how “top-down information should constrain the search for relevant dimensions/features of categorization” (sect. 3.4.2).

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14

Schubert, Thomas W., and Sabine Otten. "Overlap of Self, Ingroup, and Outgroup: Pictorial Measures of Self-Categorization." Self and Identity 1, no. 4 (October 2002): 353–76. http://dx.doi.org/10.1080/152988602760328012.

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15

Willer, David, John C. Turner, Michael A. Hogg, Penelope J. Oakes, Stephen D. Reicher, and Margaret S. Wetherell. "Rediscovering the Social Group: A Self-Categorization Theory." Contemporary Sociology 18, no. 4 (July 1989): 645. http://dx.doi.org/10.2307/2073157.

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16

Li, Liang Jun, Bin Zhang, Yuan Yuan Che, Ming Yang, and Tie Nan Li. "Self-Adaptive Weighting Text Association Categorization Algorithm Research." Advanced Materials Research 171-172 (December 2010): 246–51. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.246.

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In text association classification research, feature distribution of the training sample collection impacts greatly on the classification results, even with a same classification algorithm classification results will have obvious differences using different sample collections. In order to solve the problem, the stability of association classification is improved by the weighing method in the paper, the design realizes the association classification algorithms (WARC) based on rule weight. In the WARC algorithm, this paper proposes the concept of classification rule intensity and gives the concrete formula. Using rule intensity defines the rule adjustment factors that adjust uneven classification rules. Experimental results show the accuracy of text classification can be improved obviously by self-adaptive weighting.

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17

Johnson, Melissa A. "Incorporating Self-Categorization Concepts Into Ethnic Media Research." Communication Theory 20, no. 1 (February 2010): 106–25. http://dx.doi.org/10.1111/j.1468-2885.2009.01356.x.

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18

Han, Jiyoung, and Christopher M. Federico. "Conflict-Framed News, Self-Categorization, and Partisan Polarization." Mass Communication and Society 20, no. 4 (April 11, 2017): 455–80. http://dx.doi.org/10.1080/15205436.2017.1292530.

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19

Tarrant, Mark, and Kathyrn Butler. "Effects of self-categorization on orientation towards health." British Journal of Social Psychology 50, no. 1 (March 2011): 121–39. http://dx.doi.org/10.1348/014466610x511645.

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20

REID, FRASER. "Rediscovering the Social Group: A Self-Categorization Theory." British Journal of Social Psychology 26, no. 4 (December 1987): 347–48. http://dx.doi.org/10.1111/j.2044-8309.1987.tb00799.x.

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21

Zhang, Jinguang, and Scott A. Reid. "A Self-Categorization Explanation for Opinion Consensus Perceptions." Human Communication Research 39, no. 3 (May 22, 2013): 269–94. http://dx.doi.org/10.1111/hcre.12004.

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22

Chen, Hsinchun, Chris Schuffels, and Richard Orwig. "Internet Categorization and Search: A Self-Organizing Approach." Journal of Visual Communication and Image Representation 7, no. 1 (March 1996): 88–102. http://dx.doi.org/10.1006/jvci.1996.0008.

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23

Verkuyten, Maykel. "Self-categorization and the explanation of ethnic discrimination." Journal of Community & Applied Social Psychology 8, no. 6 (November 1998): 395–407. http://dx.doi.org/10.1002/(sici)1099-1298(199811/12)8:6<395::aid-casp475>3.0.co;2-3.

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24

Chattopadhyay, Prithviraj, Elizabeth George, and Sandra A. Lawrence. "Why Does Dissimilarity Matter? Exploring Self-Categorization, Self-Enhancement, and Uncertainty Reduction." Journal of Applied Psychology 89, no. 5 (2004): 892–900. http://dx.doi.org/10.1037/0021-9010.89.5.892.

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25

VAN QUAQUEBEKE, NIELS, and DAAN VAN KNIPPENBERG. "Second-Generation Leader Categorization Research: How Subordinates' Self- and Typical Leader Perceptions Moderate Leader Categorization Effects." Journal of Applied Social Psychology 42, no. 6 (March 28, 2012): 1293–319. http://dx.doi.org/10.1111/j.1559-1816.2012.00899.x.

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26

Van Raalte, Judy L., Allen E. Cornelius, Maureen K. Copeskey, and Britton W. Brewer. "Say What? An Analysis of Spontaneous Self-Talk Categorization." Sport Psychologist 28, no. 4 (December 2014): 390–93. http://dx.doi.org/10.1123/tsp.2014-0017.

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Research exploring spontaneously generated self-talk has involved recording performers’ self-talk categorized by researchers. The actor-observer bias, suggests that actors (performers) and observers (researchers) may perceive the same situation (e.g., self-talk) differently. The purpose of this study was to explore the actor-observer bias and validity of self-talk categorization. College students’ (n = 30) spontaneous self-talk was audio recorded during a dart throwing task. Participants then listened to and categorized their self-talk. Three independent researchers reviewed written transcripts and categorized the self-talk. Another three researchers who had not read the transcripts listened to audio recordings and categorized the same self-talk. Results confirmed actor-observer bias predictions. Spontaneous self-talk ratings made by participants were similar to but distinct from those made by researchers reading transcripts or listening to self-talk audio recordings. These results suggest that participant categorization of spontaneous self-talk may be a valid strategy to enhance understanding of self-talk used in competitive settings.

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27

Gjerdingen, Robert O. "Categorization of Musical Patterns by Self-Organizing Neuronlike Networks." Music Perception 7, no. 4 (1990): 339–69. http://dx.doi.org/10.2307/40285472.

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Simulations of self-organizing neuronlike networks are used to demonstrate how untrained listeners might be able to sort their perceptions of dozens of diverse musical features into stable, meaningful schemata. A presentation is first made of the salient characteristics of such networks, especially the adaptive- resonance-theory (ART) networks proposed by Stephen Grossberg. Then a discussion follows of how a computer simulation of a four-level ART network—a simulation dubbed L'ART pour l'art—independently categorized musical events in Mozart's six earliest compositions. The ability of the network to abstract significant voiceleading combinations from these pieces (and in fact to detect a possible error in the New Mozart Edition) suggests that this approach holds promise for the study of how ordinary listeners process music's multidimensional complexity. In addition, the categorizations produced by the network are suggestive of alternative conceptualizations of music's hierarchical structure.

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28

Hogg, Michael A., and Deborah J. Terry. "Social Identity and Self-Categorization Processes in Organizational Contexts." Academy of Management Review 25, no. 1 (January 2000): 121. http://dx.doi.org/10.2307/259266.

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29

Hogg, Michael A., and Deborah I. Terry. "Social Identity and Self-Categorization Processes in Organizational Contexts." Academy of Management Review 25, no. 1 (January 2000): 121–40. http://dx.doi.org/10.5465/amr.2000.2791606.

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30

A. Johnson, Melissa, and William Sink. "Ethnic Museum Websites, Cultural Projection, and Self-Categorization Concepts." Howard Journal of Communications 26, no. 2 (April 3, 2015): 206–25. http://dx.doi.org/10.1080/10646175.2015.1014981.

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31

Hogg, Machael A., John C. Turner, Clelia Nascimento-Schulze, and David Spriggs. "Social Categorization, Intergroup Behaviour and Self-Esteem: Two Experiments." Revista de Psicología Social 1, no. 1 (January 1986): 23–37. http://dx.doi.org/10.1080/02134748.1986.10821541.

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32

Reid, Scott A., and Michael A. Hogg. "A Self-Categorization Explanation for the Third-Person Effect." Human Communication Research 31, no. 1 (January 2005): 129–61. http://dx.doi.org/10.1111/j.1468-2958.2005.tb00867.x.

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33

Reid, Scott A. "A Self-Categorization Explanation for the Hostile Media Effect." Journal of Communication 62, no. 3 (April 24, 2012): 381–99. http://dx.doi.org/10.1111/j.1460-2466.2012.01647.x.

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34

Levine, Mark, Clare Cassidy, Gemma Brazier, and Stephen Reicher. "Self-Categorization and Bystander Non-intervention: Two Experimental Studies1." Journal of Applied Social Psychology 32, no. 7 (July 2002): 1452–63. http://dx.doi.org/10.1111/j.1559-1816.2002.tb01446.x.

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35

Grossberg, Stephen. "Self-organizing neural models of categorization, inference and synchrony." Behavioral and Brain Sciences 16, no. 3 (September 1993): 460–61. http://dx.doi.org/10.1017/s0140525x00031034.

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36

Ray, Devin G., Diane M. Mackie, Robert J. Rydell, and Eliot R. Smith. "Changing categorization of self can change emotions about outgroups." Journal of Experimental Social Psychology 44, no. 4 (July 2008): 1210–13. http://dx.doi.org/10.1016/j.jesp.2008.03.014.

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37

Webber, Richard. "The limits to personal self-categorization on key demographics." International Journal of Market Research 60, no. 3 (May 2018): 228–31. http://dx.doi.org/10.1177/1470785318766181.

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Any research survey is likely to apply some set of rules in order to classify respondents according to age, gender, social class, ethnicity, disability, and so on. But the rules governing how people are categorized may be less consistent than we suppose. In respect of gender and ethnicity, there is an unspoken assumption that the researcher should accept unquestioningly the category with which the data subject self-identifies. But in respect of social class, an equally important aspect of identity, respondents are content to have categories applied externally, for example, on the basis of their occupation. The article argues that rather than seeking to achieve a supposedly “correct” classification for each data subject, it might be better to apply at least two categorizations, one reflecting a person’s own self-identification, the other on how they are socially perceived. These different forms of identification are relevant to different types of research application.

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38

Fetterman, Adam K., Michael D. Robinson, and Elizabeth P. Gilbertson. "Implicit Self-Importance in an Interpersonal Pronoun Categorization Task." Current Psychology 33, no. 2 (January 21, 2014): 185–98. http://dx.doi.org/10.1007/s12144-014-9205-x.

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39

Day, David V., William E. Cross, Erika L. Ringseis, and Tamara L. Williams. "Self-Categorization and Identity Construction Associated with Managing Diversity." Journal of Vocational Behavior 54, no. 1 (February 1999): 188–95. http://dx.doi.org/10.1006/jvbe.1998.1648.

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40

Verkuyten, Maykel, and Shervin Nekuee. "Self-Esteem, Discrimination, and Coping Among Refugees: The Moderating Role of Self-Categorization." Journal of Applied Social Psychology 31, no. 5 (May 2001): 1058–75. http://dx.doi.org/10.1111/j.1559-1816.2001.tb02662.x.

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41

Forehand, Mark R., and Rohit Deshpandé. "What We See Makes Us who We are: Priming Ethnic Self-Awareness and Advertising Response." Journal of Marketing Research 38, no. 3 (August 2001): 336–48. http://dx.doi.org/10.1509/jmkr.38.3.336.18871.

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The authors propose that “ethnic self-awareness”—a temporary state during which a person is more sensitive to information related to his or her own ethnicity—moderates consumer response to targeted advertising. Ethnic self-awareness occurs when a person engages in a process of self-categorization and uses ethnic criteria as the basis for this categorization. The authors hypothesize that “ethnic primes”—visual or verbal cues that draw attention to ethnicity—direct self-categorization and increase ethnic self-awareness. To test these hypotheses, the authors conduct two experiments. Using 109 Asian and Caucasian participants, Experiment 1 assessed the impact of exposure to an Asian ethnic prime on ethnic self-awareness and on response to targeted television advertising. Exposure to an ethnic prime increased the rate at which participants spontaneously mentioned their ethnicity in self-descriptions (a measure of ethnic self-awareness) and caused participants to respond more favorably to same-ethnicity spokespeople and advertising that targeted their ethnicity. Experiment 2 tested the theory in a print advertising context and extended the design by manipulating the type of ethnic prime participants saw (Asian or Caucasian) and the market that the focal advertisement targeted (Asian or Caucasian). Experiment 2 replicated the findings of Experiment 1 when the focal advertisement targeted Asians, but not when it targeted Caucasians.

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42

Hadden, Benjamin W., S. Marie Harvey, Richard A. Settersten, and Christopher R. Agnew. "What Do I Call Us? The Investment Model of Commitment Processes and Changes in Relationship Categorization." Social Psychological and Personality Science 10, no. 2 (March 20, 2018): 235–43. http://dx.doi.org/10.1177/1948550617745115.

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The investment model of commitment has been used to understand relationship maintenance and dissolution across a variety of populations and relationship types. The current study used data from the Project on Partner Dynamics (POPD), a cohort study of young adults involved in nonmarital sexual relationships in the Los Angeles area, to test whether and how the investment model of commitment processes predicts individuals' self-reported categorizations of their relationships over time. We examined (1) how relationship categorizations are associated with variables outlined by the investment model and (2) whether model variables predict changes in relationship categorization over time. We found that changes in relationship self-categorization were associated with simultaneous changes in investment model variables, and that the model largely predicts the likelihood of future changes in relational self-categorization. These results are the first to examine how the investment model prospectively predicts the progression or regression of relationships beyond relationship dissolution.

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43

유여란. "The Use of Membership Categorization Devices for Self-praise Avoidance." Discourse and Cognition 22, no. 2 (August 2015): 75–99. http://dx.doi.org/10.15718/discog.2015.22.2.75.

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44

Hornsey, Matthew J. "Social Identity Theory and Self-categorization Theory: A Historical Review." Social and Personality Psychology Compass 2, no. 1 (January 2008): 204–22. http://dx.doi.org/10.1111/j.1751-9004.2007.00066.x.

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45

Jain, Shailendra Pratap, Kalpesh Kaushik Desai, and Huifang Mao. "The Influence of Chronic and Situational Self-Construal on Categorization." Journal of Consumer Research 34, no. 1 (June 2007): 66–76. http://dx.doi.org/10.1086/513047.

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46

Hogg, Michael A., and Elizabeth A. Hardie. "Social Attraction, Personal Attraction, and Self-Categorization-, A Field Study." Personality and Social Psychology Bulletin 17, no. 2 (April 1991): 175–80. http://dx.doi.org/10.1177/014616729101700209.

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47

Hogg, Michael A., and Scott A. Reid. "Social Identity, Self-Categorization, and the Communication of Group Norms." Communication Theory 16, no. 1 (February 2006): 7–30. http://dx.doi.org/10.1111/j.1468-2885.2006.00003.x.

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48

Suleiman, Ramzi. "Minority self-categorization: The case of the Palestinians in Israel." Peace and Conflict: Journal of Peace Psychology 8, no. 1 (March 2002): 31–46. http://dx.doi.org/10.1207/s15327949pac0801_4.

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49

Guzmán-Cabrera, Rafael, Manuel Montes-y-Gómez, Paolo Rosso, and Luis Villaseñor-Pineda. "Using the Web as corpus for self-training text categorization." Information Retrieval 12, no. 3 (December 23, 2008): 400–415. http://dx.doi.org/10.1007/s10791-008-9083-7.

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50

CHEN, WENLIANG, JINGBO ZHU, MUHUA ZHU, LI ZHANG, and TIANSHUN YAO. "Improving Domain Dictionary-Based Text Categorization Using Self-Partition Model." International Journal of Computer Processing of Languages 18, no. 03 (September 2005): 197–210. http://dx.doi.org/10.1142/s0219427905001304.

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