Measuring social complexity

被引:109
|
作者
Bergman, Thore J. [1 ,2 ]
Beehner, Jacinta C. [1 ,3 ]
机构
[1] Univ Michigan, Dept Psychol, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USA
[3] Univ Michigan, Dept Anthropol, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
cognition; differentiated relationships; evolution; intelligence; social complexity hypothesis; FISSION-FUSION DYNAMICS; BOTTLE-NOSED DOLPHINS; BRAIN-SIZE EVOLUTION; FOOD-STORING BIRDS; NEOCORTEX SIZE; INDIVIDUAL RECOGNITION; PRIMATES; INTELLIGENCE; HYPOTHESIS; RANK;
D O I
10.1016/j.anbehav.2015.02.018
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
In one of the first formulations of the social complexity hypothesis, Humphrey (1976, page 316, Growing Points in Ethology, Cambridge University Press) predicts 'that there should be a positive correlation across species between social complexity and individual intelligence'. However, in the many ensuing tests of the hypothesis, surprisingly little consideration has been given to measures of the independent variable in this evolutionary relationship, that is, social complexity. Here, we seek to encourage more rigorous measures of social complexity. We first review previous definitions of this variable and point to two common flaws; a lack of objectivity and a failure to directly connect sociality to the use of cognition. We argue that, rather than creating circularity, including cognition in the definition of social complexity is necessary for accurately testing the social complexity hypothesis. We propose a new definition of social complexity that is based on the number of differentiated relationships that individuals have. We then demonstrate that the definition is both broadly applicable and flexible, allowing researchers to include more detailed information about the degree of differentiation among individuals when the data are available. While we see this definition of social complexity as one possible way forward, our larger goal is to encourage researchers examining the social complexity hypothesis to carefully consider their measurement of social complexity. (C) 2015 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:203 / 209
页数:7
相关论文
共 50 条
  • [1] Measuring the complexity of social associations using mixture models
    Weiss, Michael N.
    Franks, Daniel W.
    Croft, Darren P.
    Whitehead, Hal
    [J]. BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY, 2019, 73 (01)
  • [2] Metrics for measuring complexity and completeness for social goal models
    Gralha, Catarina
    Araujo, Joao
    Goulao, Miguel
    [J]. INFORMATION SYSTEMS, 2015, 53 : 346 - 362
  • [3] Measuring the complexity of social associations using mixture models
    Michael N. Weiss
    Daniel W. Franks
    Darren P. Croft
    Hal Whitehead
    [J]. Behavioral Ecology and Sociobiology, 2019, 73
  • [4] The complexity of measuring complexity
    Ivan Tarride, Mario
    [J]. KYBERNETES, 2013, 42 (1-2) : 174 - 184
  • [5] The Complexity of Measuring Clinical Complexity
    Turner, Barbara J.
    Cuttler, Leona
    [J]. ANNALS OF INTERNAL MEDICINE, 2011, 155 (12) : 851 - U103
  • [6] WHAT IS SCIENTIFIC ABOUT SOCIAL SCIENCE? THE COMPLEXITY OF MEASURING HUMAN BEHAVIOR
    Priest, Susanna
    [J]. METODE-POPULAR SCIENCE JOURNAL, 2015, (05): : 201 - 207
  • [7] Measuring complexity by measuring structure and organization
    Hornby, Gregory S.
    [J]. 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 2017 - 2024
  • [8] Measuring complexity with zippers
    Baronchelli, A
    Caglioti, E
    Loreto, V
    [J]. EUROPEAN JOURNAL OF PHYSICS, 2005, 26 (05) : S69 - S77
  • [9] Measuring the 'complexity' of sound
    Singh, Nandini Chatterjee
    [J]. PRAMANA-JOURNAL OF PHYSICS, 2011, 77 (05): : 811 - 816
  • [10] Measuring map complexity
    Fairbairn, David
    [J]. CARTOGRAPHIC JOURNAL, 2006, 43 (03): : 224 - 238