Relevant bibliographies by topics / Categorization (Psychology)

Academic literature on the topic 'Categorization (Psychology)'

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Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Categorization (Psychology)"

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Chater, Nick. "Categorization, theories and folk psychology." Behavioral and Brain Sciences 16, no. 1 (March 1993): 37. http://dx.doi.org/10.1017/s0140525x00028739.

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Vandierendonck, André. "Cognitive Psychology: Variations on Categorization." Contemporary Psychology: A Journal of Reviews 39, no. 1 (January 1994): 53–54. http://dx.doi.org/10.1037/033811.

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Pothos, Emmanuel M., and Nick Chater. "Unsupervised Categorization and Category Learning." Quarterly Journal of Experimental Psychology Section A 58, no. 4 (May 2005): 733–52. http://dx.doi.org/10.1080/02724980443000322.

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When people categorize a set of items in a certain way they often change their perceptions for these items so that they become more compatible with the learned categorization. In two experiments we examined whether such changes are extensive enough to change the unsupervised categorization for the items—that is, the categorization of the items that is considered more intuitive or natural without any learning. In Experiment 1 we directly employed an unsupervised categorization task; in Experiment 2 we collected similarity ratings for the items and inferred unsupervised categorizations using Pothos and Chater's (2002) model of unsupervised categorization. The unsupervised categorization for the items changed to resemble more the learned one when this was specified by the suppression of a stimulus dimension (both experiments), but less so when it was almost specified by the suppression of a stimulus dimension (Experiment 1, nonsignificant trend in Experiment 2). By contrast, no changes in the unsupervised categorization were observed when participants were taught a classification that was specified by a more fine tuning of the relative salience of the two dimensions.
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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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Nicolas, Gandalf, Allison L. Skinner, and Cheryl L. Dickter. "Other Than the Sum: Hispanic and Middle Eastern Categorizations of Black–White Mixed-Race Faces." Social Psychological and Personality Science 10, no. 4 (June 29, 2018): 532–41. http://dx.doi.org/10.1177/1948550618769591.

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The racial categorization literature, reliant on forced-choice tasks, suggests that mixed-race targets are often categorized using the parent faces that created the racially mixed stimuli (e.g., Black or White) or their combination (e.g., Black–White multiracial). In the current studies, we introduce a free-response task that allows for spontaneous categorizations of higher ecological validity. Our results suggest that, when allowed, observers often classify Black–White faces into alternative categories (i.e., responses that are neither the parent races nor their combination), such as Hispanic and Middle Eastern. Furthermore, we find that the stereotypes of the various categories that are mapped to racially mixed faces are distinct, underscoring the importance of understanding how mixed-race targets are spontaneously categorized. Our findings speak to the challenges associated with racial categorization in an increasingly racially diverse population, including discrepancies between target racial identities and their racial categorizations by observers as well as variable stereotype application to mixed-race targets.
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Loken, Barbara. "Consumer Psychology: Categorization, Inferences, Affect, and Persuasion." Annual Review of Psychology 57, no. 1 (January 2006): 453–85. http://dx.doi.org/10.1146/annurev.psych.57.102904.190136.

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Chen, Jacqueline M., Maria Clara P. de Paula Couto, Airi M. Sacco, and Yarrow Dunham. "To Be or Not to Be (Black or Multiracial or White)." Social Psychological and Personality Science 9, no. 7 (August 28, 2017): 763–72. http://dx.doi.org/10.1177/1948550617725149.

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Culture shapes the meaning of race and, consequently, who is placed into which racial categories. Three experiments conducted in the United States and Brazil illustrated the cultural nature of racial categorization. In Experiment 1, a target’s racial ancestry influenced Americans’ categorizations but had no impact on Brazilians’ categorizations. Experiment 2 showed cultural differences in the reliance on two phenotypic cues to race; Brazilians’ categorizations were more strongly determined by skin tone than were Americans’ categorizations, and Americans’ categorizations were more strongly determined by other facial features compared to Brazilians' categorizations. Experiment 3 demonstrated cultural differences in the motivated use of racial categories. When the racial hierarchy was threatened, only Americans more strictly enforced the Black–White racial boundary. Cultural forces shape the conceptual, perceptual, and ideological construal of racial categories.
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Çoşkun, Filiz, Zeynep Ceyda Sayalı, Emine Gürbüz, and Fuat Balcı. "Optimal time discrimination." Quarterly Journal of Experimental Psychology 68, no. 2 (February 2015): 381–401. http://dx.doi.org/10.1080/17470218.2014.944921.

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In the temporal bisection task, participants categorize experienced stimulus durations as short or long based on their similarity to previously acquired reference durations. Reward maximization in this task requires integrating endogenous timing uncertainty as well as exogenous probabilities of the reference durations into temporal judgements. We tested human participants on the temporal bisection task with different short and long reference duration probabilities (exogenous probability) in two separate test sessions. Incorrect categorizations were not penalized in Experiment 1 but were penalized in Experiment 2, leading to different levels of stringency in the reward functions that participants tried to maximize. We evaluated the judgements within the framework of optimality. Our participants adapted their choice behaviour in a nearly optimal fashion and earned nearly the maximum possible expected gain they could attain given their level of endogenous timing uncertainty and exogenous probabilities in both experiments. These results point to the optimality of human temporal risk assessment in the temporal bisection task. The long categorization response times (RTs) were overall faster than short categorization RTs, and short but not long categorization RTs were modulated by reference duration probability manipulations. These observations suggested an asymmetry between short and long categorizations in the temporal bisection task.
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Förster, Jens, Janina Marguc, and Marleen Gillebaart. "Novelty Categorization Theory." Social and Personality Psychology Compass 4, no. 9 (September 2010): 736–55. http://dx.doi.org/10.1111/j.1751-9004.2010.00289.x.

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Smallman, Rachel, and Neal J. Roese. "Preference Invites Categorization." Psychological Science 19, no. 12 (December 2008): 1228–32. http://dx.doi.org/10.1111/j.1467-9280.2008.02229.x.

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Past research indicates that positive affect (relative to neutral or negative affect) reduces processing and makes categorization less differentiated. The present experiment demonstrated that preference, even though affectively pleasant, invites finer categorization. Expertise is already known to influence categorization; hence, the present experiment used an associative conditioning task (novel symbols paired with positively or negatively valenced photographs) to create new preferences, thereby demonstrating that preference influences categorization independently of preexisting expertise. These findings cast new light on established theory of affect and cognitive processing and suggest new implications for consumer preference and goal pursuit.
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Dissertations / Theses on the topic "Categorization (Psychology)"

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Stewart, Neil. "Perceptual categorization." Thesis, University of Warwick, 2001. http://wrap.warwick.ac.uk/36672/.

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The categorization of external stimuli lies at the heart of cognitive science. Existing models of perceptual categorization assume (a) information about the absolute magnitude of a stimulus is used in the categorization decision, and (b) the representation of a stimulus does not change with experience. The three experimental programs presented here challenge these two assumptions. The experiments in Chapter 2 demonstrate that existing models of categorization are unable to predict the classification of items intermediate between two categories. Chapter 3 provides empirical evidence that categorization responses are heavily influenced by the immediately preceding context, consistent with evidence from absolute identification showing people have very poor access to absolute magnitude information. A memory and contrast model is presented where each categorization decision is based on the perceived difference between the current stimulus and immediately preceding stimuli. This model is shown to account for the data from Chapters 2 and 3. Chapter 4 explores the claim that new features may be created on experience with novel stimuli, and that these features serve to alter the representation of stimuli to facilitate new categorization tasks. An alternative account is offered for existing feature creation evidence. However, experimental work re-establishes a feature creation effect. Consideration is given as to how feature creation and memory and contrast accounts of categorization may be integrated, together with extensive suggestions for the development of these ideas.
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Zhang, Hanshu. "Processing global properties in Scene Categorization." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495799774568591.

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Deng, Wei. "The Role of Linguistic Labels in Categorization." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306871100.

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Yang, Lee-Xieng. "Knowledge partitioning in categorization." University of Western Australia. School of Psychology, 2004. http://theses.library.uwa.edu.au/adt-WU2005.0016.

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Christy, Kristin N. "Generalization within an implicit categorization task." Oxford, Ohio : Miami University, 2003. http://www.ohiolink.edu/etd/view.cgi?miami1060840327.

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Sun, Jie. "Object categorization for affordance prediction." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24625.

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Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009.
Committee Chair: Rehg, James M.; Committee Co-Chair: Bobick, Aaron; Committee Member: Balch, Tucker; Committee Member: Christensen, Henrik I.; Committee Member: Pietro Perona
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Ferland, Mark B. "Infants' categorization of melodic contour." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=74028.

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Dial, Lauren Ann. "Healthy? Tasty? Children's Evaluative Categorization of Novel Foods." Bowling Green State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1518364823958472.

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Falk, Robert S. "Sociometric Categorization of Children: An Empirically Based Method." VCU Scholars Compass, 1988. http://scholarscompass.vcu.edu/etd/4717.

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The use of sociometric assessment as a method for investigating the social competence of children and the prediction of future adjustment difficulties was reviewed. Recent methods used to form up to five sociometric groups (Popular, Average, Rejected, Neglected, and Controversial) were surveyed. Various combinations of raw scores, standard deviation units, standardized scores, and binomial probability scores have been used in classification procedures. lnclusion/exclusion criteria, or cutoff scores, have been based on arbitrary statistical decisions regarding the ”extremeness" of children’s statements (positive and negative nominations) regarding their peers. These aspects of sociometric categorization result in limitations on the validity and generalizability of research in the area. The current study attempted to develop an empirically based categorization system to remedy limitations to sociometric research. Four components made up the study. The relationship between a set of teacher-reported behavioral descriptors and continuous sociometric data was determined. Second, contingent-frequency tables for the behavioral descriptors most strongly associated with the sociometric data were developed. Third, cutting scores to maximize the behavioral homogeneity of sociometric groups were determined from this information. Finally, the efficiency of binomial scores in classifying children sociometrically was compared to that achieved by arbitrary classification schemes. An empirically based method for sociometric categorization was developed which differed significantly from previously devised methods. Discriminant function analyses for the new method and two arbitrary methods were performed to assess the prediction of Average, Popular, and Rejected groups from parent ratings. No significant difference was found between the three methods’ ability to correctly classify cases into one of the three groups with parent ratings as predictor variables. However, two important groups (Neglected and Controversial children) were deleted from the comparison because of inadequate size. This placed an unintended limit on the validational comparison. Advantages of an empirical approach to sociometric classification and implications of the study are discussed in terms of the cognitive psychological concept of prototypes. Limitations of the current study together with possible directions for future research are presented.
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Gyurovski, Ivo Ivanov. "Spontaneous Categorization: Assessment of Implicit Stereotype Content Awareness." W&M ScholarWorks, 2011. https://scholarworks.wm.edu/etd/1539626670.

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Books on the topic "Categorization (Psychology)"

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1963-, Hahn Ulrike, and Ramscar Michael, eds. Similarity and categorization. Oxford: Oxford University Press, 2001.

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Françoise, Cordier. Les représentations cognitives privilégiés: Typicalité et niveau de base. [Lille]: Presses universitaires de Lille, 1993.

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Møller, Marie Østergaard. Solidarity and categorization: Solidarity perceptions and categorization practices among Danish social workers. Århus: Politica, 2009.

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Georges, Vignaux. Le démon du classement: Penser et organiser. Paris: Seuil, 1999.

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Pottier, Bernard. Représentations mentales et catégorisations linguistiques. Leuven, Belgium: Peeters, 2000.

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1973-, Crisp Richard J., and Hewstone Miles, eds. Multiple social categorization: Processes, models, and applications. Hove [England]: Psychology Press, 2006.

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Eckes, Thomas. Psychologie der Begriffe: Strukturen des Wissens und Prozesse der Kategorisierung. Göttingen: Hogrefe, 1991.

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1945-, Cohen Henri, and Lefebvre Claire, eds. Handbook of categorization in cognitive science. Amsterdam: Elsevier, 2005.

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Edinburgh), SimCat 1997 (Conference) (1997 University of. Proceedings of SimCat 1997: An interdisciplinary workshop on similarity and categorisation, November 28-30, 1997, Edinburgh University. Edinburgh: Department of Artificical Intelligence, Edinburgh University, 1997.

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H, Oscar Jara. Para sistematizar experiencias. San José, Costa Rica: ALFORJA, 1994.

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Book chapters on the topic "Categorization (Psychology)"

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Nokeri, Tshepo Chris. "Medical Records Categorization." In Artificial Intelligence in Medical Sciences and Psychology, 131–44. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8217-5_8.

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Kite, Mary E., Bernard E. Whitley, and Lisa S. Wagner. "Social Categorization and Stereotypes." In Psychology of Prejudice and Discrimination, 97–142. 4th ed. New York: Routledge, 2022. http://dx.doi.org/10.4324/9780367809218-3.

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Rosch, Eleanor. "Wittgenstein and Categorization Research in Cognitive Psychology." In Meaning and the Growth of Understanding, 151–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83023-5_9.

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Hogg, Michael A. "Social Categorization, Depersonalization, and Group Behavior." In Blackwell Handbook of Social Psychology: Group Processes, 56–85. Oxford, UK: Blackwell Publishers Ltd, 2008. http://dx.doi.org/10.1002/9780470998458.ch3.

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Aust, Ulrike. "Perceptual and functional categorization in animals." In APA handbook of comparative psychology: Perception, learning, and cognition., 89–116. Washington: American Psychological Association, 2017. http://dx.doi.org/10.1037/0000012-005.

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Smolenaars, Anton J. "An Elementary Formal Categorization of a Corpus of Spelling Errors." In Recent Research in Psychology, 197–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83943-6_13.

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Schmid, Katharina, and Miles Hewstone. "Combined Effects of Intergroup Contact and Multiple Categorization." In The Psychology of Social and Cultural Diversity, 297–321. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444325447.ch13.

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Marques, Leonel Garcia, and José Manuel Palma Oliveira. "National Identities and Levels of Categorization: Self-Stereotypes, Attitudes and Perception of Other Nationalities." In Environmental Social Psychology, 312–19. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2802-2_27.

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Franklin, Anna. "The Role of Culture and Language in the Development of Color Categorization." In Minnesota Symposia on Child Psychology, 39–81. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119301981.ch2.

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Marques, José M., Dominic Abrams, Dario Páez, and Michael A. Hogg. "Social Categorization, Social Identification, and Rejection of Deviant Group Members." In Blackwell Handbook of Social Psychology: Group Processes, 400–424. Oxford, UK: Blackwell Publishers Ltd, 2008. http://dx.doi.org/10.1002/9780470998458.ch17.

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Conference papers on the topic "Categorization (Psychology)"

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WICHERT, ANDRZEJ. "IMAGE CATEGORIZATION AND RETRIEVAL." In Proceedings of the 11th Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789812834232_0010.

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WESTERMANN, GERT, and DENIS MARESCHAL. "A DUAL-MEMORY MODEL OF CATEGORIZATION IN INFANCY." In Proceedings of the Tenth Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812797322_0011.

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WESTERMANN, G., and D. MARESCHAL. "MODELLING ASYMMETRIC INFANT CATEGORIZATION WITH THE REPRESENTATIONAL ACUITY HYPOTHESIS." In Proceedings of the Eighth Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702784_0009.

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LOPEZ, L., P. BONIN, N. VERMEULEN, A. MEOT, and M. MERMILLOD. "THE IMPORTANCE OF LOW SPATIAL FREQUENCIES FOR CATEGORIZATION OF EMOTIONAL FACIAL EXPRESSIONS." In Proceedings of the 12th Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814340359_0006.

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MERMILLOD, M., N. VERMEULEN, G. KAMINSKY, E. GENTAZ, and P. BONIN. "THEORETICAL AND COMPUTATIONAL LIMITATIONS IN SIMULATING 3- TO 4-MONTH-OLD INFANTS' CATEGORIZATION PROCESSES." In Proceedings of the 13th Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814458849_0008.

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MIROLLI, MARCO, and DOMENICO PARISI. "LANGUAGE AS AN AID TO CATEGORIZATION: A NEURAL NETWORK MODEL OF EARLY LANGUAGE ACQUISITION." In Proceedings of the Ninth Neural Computation and Psychology Workshop. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812701886_0009.

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Singla, Rashmi. "South Asians in Scandinavia: Diasporic Identity Processes." In International Association of Cross Cultural Psychology Congress. International Association for Cross-Cultural Psychology, 2009. http://dx.doi.org/10.4087/ozyx5668.

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This chapter1 probes selected social-psychological aspects for South Asian young adults in Denmark and is a follow up of a Danish project conducted in the mid-nineties. The diasporic conceptualizations in respect to human centeredness and cultural processes in migration combined with life course perspective, provide the theoretical framework for this study. In-depth interviews were employed, and information was analyzed through meaning condensation and subsequent categorization of the narratives. The results show the reinterpretation of the self, “others” and home in the diasporic families, for the parental as well as the young generation. The chapter also depicts the young adults’ diasporic identities involving the ancestral countries as well as the Scandinavian welfare societies. The results hardly support the myth of return, although the countries of residence have turned increasingly restrictive in migration policies in the past years.
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Gerasimenko, Natalia. "SEMANTIC AND PHYSICAL CHARACTERISTICS OF A DISTRACTOR INFLUENCE ON THE PROCESS OF BASIC CATEGORIZATION OF VISUAL STIMULI." In XVI International interdisciplinary congress "Neuroscience for Medicine and Psychology". LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m994.sudak.ns2020-16/144-145.

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Hu, Jun, and George M. Fadel. "Categorizing Affordances for Product Design." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70933.

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To compensate for the inability of the functional descriptions to describe for instance interactions between users and artifacts, the term affordance has been introduced in design methodology by Maier and Fadel. However, some significant details of affordance such as representation, categorization, and application to mechanical design still need to be further studied. Therefore, this paper reviews and compares the use of the term affordance in the fields of Human-Computer Interaction (HCI), Artificial Intelligence (AI), design, psychology, and philosophy. Based on that review, a new categorization scheme of affordances applicable for product design is proposed. The categories including doing and happening Artifact-Artifact Affordances (dAAA and hAAA), doing and happening Artifact-Environment Affordances (dAEA and hAEA), and doing and happening Artifact-User Affordances (dAUA and hAUA) are identified and an initial statistical evaluation is performed to support this proposal. The detailed description of these affordances provides better coverage, more orthogonality, more depth, and could be more usable, eventually meeting the requirements of a taxonomy.
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Stanciu, Ionutdorin. "ENHANCING INFORMATION PROCESSING BY USER CATEGORIZATION. TAGGING CONTENT IN SUPPORT OF LEARNING." In eLSE 2015. Carol I National Defence University Publishing House, 2015. http://dx.doi.org/10.12753/2066-026x-15-217.

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Allocating labels to an object, either physical or abstract, contributes to expanding or consolidating the meaning of that particular object, hence, the name ,,metadata" used in informatics. The structure of learning materials usually attempts to simply the categorization of their contents by creating a hierarchical structure that is reflected in chapters and sections. However, this categorization approach is both subject to the author's perspective and limited in terms of reflecting the relations between the concepts included in the learning contents. The Web 2.0 era brought the advent of a non-hierarchical contents labeling behavior, mostly referred to as tagging, and whose main original purpose was the description of contents closest to their author' original understanding, but also open to interaction with other users. This co-authoring would lead, in turn, to better indexing and search capability of the tagged contents. The main premise of our study was that increasing levels of learners' involvement in tagging learning contents delivered during academic instruction would lead to deepening of information processing. Two studies were conducted to identify supporting arguments with participants comprised of 1st year undergraduate students enrolled in the Psychology of Education course. The first study respected a between-subjects factorial post-test only design with two experimental groups and one control group. ANOVA on the three groups' results in a knowledge test illustrated statistically significant differences between the groups, corresponding to the original hypothesis and suggesting that the higher the involvement of the individual in tagging the learning content, the deeper is the learner's understanding of that content. The second study was a within-subjects repeated measures design in which the same learners were subject to a control and two modalities of tagging, corresponding to various degrees of leaner's involvement. The results also show statistically significant differences in the measured academic performance, corresponding to the initial research hypothesis. Tagging information content is now a regular practice on the web and it is also possible for e-learning digitally delivered contents. Our research suggests that the learners' involvement in tagging the contents leads to better learning outcomes. However, factors such as the learners' computer literacy and openness to digital technologies may also influence their involvement in the tagging process. Future studies, incorporating more refined research designs, can optimize the understanding of the specificity and accuracy of the observed influence.
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