Always a Bridesmaid: A Machine Learning Approach to Minor Party Identity in Multi-Party Systems
-
Laura French Bourgeois
,
Allison Harell
,
Laura Stephenson
,
Philippe Guay
Abstract
In multiparty systems, maintaining a distinct and positive partisan identity may be more difficult for those who identify with minor parties, because such parties lack the rich history of success that could reinforce a positive social standing in the political realm. Yet, we know little about the unique nature of minor partisan identities because partisanship tends to be most prominent in single-member plurality systems that tend toward two dominant parties, such as the United States. Canada provides a fascinating case of a single-member plurality electoral system that has consistently led to a multiparty system, ideal for studying minor party identity. We use large datasets of public opinion data, collected in 2019 and 2021 in Canada, to test a Lasso regression, a machine learning technique, to identify the factors that are the most important to predict whether partisans of minor political parties will seek in-group distinctiveness, meaning that they seek a different and positive political identity from the major political parties they are in competition with, or take part in out-group favouritism, meaning that they seek to become closer major political parties. We find that party rating is the most important predictor. The more partisans of the minor party rate their own party favourably, the more they take part in distinctiveness. We also find that the more minor party partisans perceive the major party as favourable, the more favouritism they will show towards the major party.
References
Abramson, P. R., J. H. Aldrich, A. Blais, M. Diamond, A. Diskin, I. H. Indridason, D. J. Lee, and R. Levine. 2010. “Comparing Strategic Voting under FPTP and PR.” Comparative Political Studies 43 (1): 61–90. https://doi.org/10.1177/0010414009341717.Suche in Google Scholar
Alvarez, R. M., and J. Nagler. 2000. “A New Approach for Modelling Strategic Voting in Multiparty Elections.” British Journal of Political Science 30 (1): 57–75. https://doi.org/10.1017/S000712340000003X.Suche in Google Scholar
Bélanger, É., and L. B. Stephenson. 2010. “Parties and Partisans: The Influence of Ideology and Brokerage on the Durability of Partisanship in Canada.” In Voting Behaviour in Canada, edited by C. D. Anderson, and L. B. Stephenson, 107–38. Vancouver: UBC press.10.59962/9780774817851-008Suche in Google Scholar
Bettencourt, B., K. Charlton, N. Dorr, and D. L. Hume. 2001. “Status Differences and In-Group Bias: A Meta-Analytic Examination of the Effects of Status Stability, Status Legitimacy, and Group Permeability.” Psychological Bulletin 127 (4): 520. https://doi.org/10.1037/0033-2909.127.4.520.Suche in Google Scholar
Blais, A. 2002. “Why Is There So Little Strategic Voting in Canadian Plurality Rule Elections?” Political Studies 50 (3): 445–54. https://doi.org/10.1111/1467-9248.00378.Suche in Google Scholar
Blais, A., and M. A. Bodet. 2006. “How Do Voters Form Expectations about the Parties’ Chances of Winning the Election?” Social Science Quarterly 87 (3): 477–93. https://doi.org/10.1111/j.1540-6237.2006.00392.x.Suche in Google Scholar
Blais, A., Dostie-Goulet, E., and Bodet, M. A. 2009. “Voting Strategically in Canada and Britain.” In Duverger’s Law of Plurality Voting: The Logic of Party Competition in Canada, India, the United Kingdom and the United States, edited by S. Bowler, A. Blais and B. Grofman, 13–25. New York: Springer.10.1007/978-0-387-09720-6_2Suche in Google Scholar
Blais, A., A. Degan, R. D. Congleton, B. N. Grofman, and S. Voigt. 2019. “The Study of Strategic Voting.” In The Oxford Handbook of Public Choice, Vol. 1, edited by R. D. Congleton, B. Grofman and S. Voigt, 292–309. New York: Oxford University Press.10.1093/oxfordhb/9780190469733.013.14Suche in Google Scholar
Blais, A., and M. Turgeon. 2004. “How Good Are Voters at Sorting Out the Weakest Candidate in Their Constituency?” Electoral Studies 23 (3): 455–61. https://doi.org/10.1016/s0261-3794(03)00031-3.Suche in Google Scholar
Brownlee, J. 2016. “Machine Learning Algorithms from Scratch with Python.” Machine Learning Mastery. v1.9Suche in Google Scholar
Campbell, A., P. E. Converse, W. E. Miller, and D. E. Stokes. 1980. Chicago and London. The American Voter: University of Chicago Press.Suche in Google Scholar
Caruana, N. J., R. M. McGregor, and L. B. Stephenson. 2015. “The Power of the Dark Side: Negative Partisanship and Political Behaviour in Canada.” Canadian Journal of Political Science/Revue Canadienne de Science Politique 48 (4): 771–89. https://doi.org/10.1017/S0008423914000882.Suche in Google Scholar
Chatterjee, A., and S. N. Lahiri. 2011. “Bootstrapping Lasso Estimators.” Journal of the American Statistical Association 106 (494): 608–25. https://doi.org/10.1198/jasa.2011.tm10159.Suche in Google Scholar
Dinas, E. 2014. “Does Choice Bring Loyalty? Electoral Participation and the Development of Party Identification.” American Journal of Political Science 58 (2): 449–65. https://doi.org/10.1111/ajps.12044.Suche in Google Scholar
Duverger, M. 1963. Political Parties: Their Organization and Activity in the Modern State, North, B. and North R., tr. New York: Wiley, Science Ed.Suche in Google Scholar
Greene, S. H. 1999. The Psychological Structure of Partisanship: Affect, Cognition, and Social Identity in Party Identification: Athens, Ohio: The Ohio State University.Suche in Google Scholar
Grofman, B., S. Bowler, and A. Blais. 2009. “Introduction: Evidence for Duverger’s Law from Four Countries.” In Duverger’s Law of Plurality Voting: The Logic of Party Competition in Canada, India, the United Kingdom and the United States, edited by B. Grofman, A. Blais, and S. Bowler, 1–11. New York: Springer Science+Business Media.10.1007/978-0-387-09720-6_1Suche in Google Scholar
Hastie, T., R. Tibshirani, and R. Tibshirani. 2020. “Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons.” Statistical Science 35 (4): 579–92. https://doi.org/10.1214/19-STS733.Suche in Google Scholar
Hetherington, M. J., M. T. Long, and T. J. Rudolph. 2016. “Revisiting the Myth: New Evidence of a Polarized Electorate.” Public Opinion Quarterly 80 (S1): 321–50. https://doi.org/10.1093/poq/nfw003.Suche in Google Scholar
Huber, G. A., and N. Malhotra. 2017. “Political Homophily in Social Relationships: Evidence from Online Dating Behavior.” The Journal of Politics 79 (1): 269–83. https://doi.org/10.1086/687533.Suche in Google Scholar
Huddy, L., and A. Bankert. 2017. “Political Partisanship as a Social Identity.” In Oxford Research Encyclopedia of Politics. New York: Oxford University Press.10.1093/acrefore/9780190228637.013.250Suche in Google Scholar
Huddy, L., L. Mason, and L. Aarøe. 2015. “Expressive Partisanship: Campaign Involvement, Political Emotion, and Partisan Identity.” American Political Science Review 109 (1): 1–17. https://doi.org/10.1017/s0003055414000604.Suche in Google Scholar
Iyengar, S., G. Sood, and Y. Lelkes. 2012. Affect, Not Ideology: A Social Identity Perspective on Polarization: Erratum.10.1093/poq/nfs038Suche in Google Scholar
Maggiotto, M. A., and J. E. Piereson. 1977. “Partisan Identification and Electoral Choice: The Hostility Hypothesis.” American Journal of Political Science 21 (4): 745–67. https://doi.org/10.2307/2110735.Suche in Google Scholar
Mason, L. 2018. Uncivil Agreement: How Politics Became Our Identity: University of Chicago Press.10.7208/chicago/9780226524689.001.0001Suche in Google Scholar
Michael McGregor, R., N. J. Caruana, and L. B. Stephenson. 2015. “Negative Partisanship in a Multi-Party System: The Case of Canada.” Journal of Elections, Public Opinion, and Parties 25 (3): 300–16. https://doi.org/10.1080/17457289.2014.997239.Suche in Google Scholar
Mullen, B., R. Brown, and C. Smith. 1992. “Ingroup Bias as a Function of Salience, Relevance, and Status: An Integration.” European Journal of Social Psychology 22 (2): 103–22. https://doi.org/10.1002/ejsp.2420220202.Suche in Google Scholar
Muthukrishnan, R., and Rohini, R. 2016. “LASSO: A Feature Selection Technique in Predictive Modeling for Machine Learning.” In 2016 IEEE International Conference on Advances in Computer Applications (ICACA), 18–20.10.1109/ICACA.2016.7887916Suche in Google Scholar
Oldmeadow, J. A., and S. T. Fiske. 2010. “Social Status and the Pursuit of Positive Social Identity: Systematic Domains of Intergroup Differentiation and Discrimination for High-and Low-Status Groups.” Group Processes & Intergroup Relations 13 (4): 425–44. https://doi.org/10.1177/1368430209355650.Suche in Google Scholar
Reichl, A. J. 1997. “Ingroup Favouritism and Outgroup Favouritism in Low Status Minimal Groups: Differential Responses to Status-Related and Status-Unrelated Measures.” European Journal of Social Psychology 27 (6): 617–33. https://doi.org/10.1002/(SICI)1099-0992(199711/12)27:6<617::AID-EJSP829>3.0.CO;2-T.10.1002/(SICI)1099-0992(199711/12)27:6<617::AID-EJSP829>3.0.CO;2-TSuche in Google Scholar
Richardson, B. M. 1991. “European Party Loyalties Revisited.” American Political Science Review 85 (3): 751–75. https://doi.org/10.2307/1963849.Suche in Google Scholar
Rothbart, M., and Lewis, S. H. 1994. “Cognitive Processes and Intergroup Relations: A Historical Perspective.” In Social Cognition: Impact on Social Psychology, edited by P. G. Devine, D. L. Hamilton and T. M. Ostrom, 347–82. Amsterdam: Academic Press.Suche in Google Scholar
Sachdev, I., and R. Y. Bourhis. 1985. “Social Categorization and Power Differentials in Group Relations.” European Journal of Social Psychology 15 (4): 415–34. https://doi.org/10.1002/ejsp.2420150405.Suche in Google Scholar
Sachdev, I., and R. Y. Bourhis. 1987. “Status Differenttals and Intergroup Behaviour.” European Journal of Social Psychology 17 (3): 277–93. https://doi.org/10.1002/ejsp.2420170304.Suche in Google Scholar
Sachdev, I., and R. Y. Bourhis. 1991. “Power and Status Differentials in Minority and Majority Group Relations.” European Journal of Social Psychology 21 (1): 1–24. https://doi.org/10.1002/ejsp.2420210102.Suche in Google Scholar
Samara Canada. 2020. First Past the Post. Also available at https://www.samaracanada.com/samara-in-the-classroom/electoral-reform/first-past-the-post/.Suche in Google Scholar
Sani, G., and G. Sartori. 1983. Polarization, Fragmentation, and Competition in Western European Democracies: Op. Cit. London: Sage.Suche in Google Scholar
Stephenson, L. B., A. Harell, D. Rubenson and P. J. Loewen. 2020. 2019 Canadian Election Study – Online Survey. Harvard Dataverse, V1. https://doi.org/10.7910/DVN/DUS88V.Suche in Google Scholar
Stephenson, L. B., A. Harell, D. Rubenson, and P. J. Loewen. 2022. 2021 Canadian Election Study. Harvard Dataverse, V1. https://doi.org/10.7910/DVN/XBZHKC.Suche in Google Scholar
Tajfel, H. ed. 1978. Differentiation between Social Groups: Studies in the Social Psychology of Intergroup Relations, xv, 474: London: Academic Press.Suche in Google Scholar
Taylor, D. M., and F. M. Moghaddam. 1994. Theories of Intergroup Relations: International Social Psychological Perspectives. Westport: Greenwood Publishing Group.Suche in Google Scholar
Tibshirani, R. 1996. Bias, Variance and Prediction Error for Classification Rules. Toronto, Canada: University of Toronto.Suche in Google Scholar
Von Hippel, C. D. 2006. “When People Would rather Switch Than Fight: Out-Group Favoritism Among Temporary Employees.” Group Processes & Intergroup Relations 9 (4): 533–46. https://doi.org/10.1177/1368430206067556.Suche in Google Scholar
West, E. A., and S. Iyengar. 2022. “Partisanship as a Social Identity: Implications for Polarization.” Political Behavior 44 (2): 807–38. https://doi.org/10.1007/s11109-020-09637-y.Suche in Google Scholar
Wulff, J. N., and L. E. Jeppesen. 2017. “Multiple Imputation by Chained Equations in Praxis: Guidelines and Review.” Electronic Journal of Business Research Methods 15 (1): 41–56.Suche in Google Scholar
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Artikel in diesem Heft
- Frontmatter
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- The Chinese Debt Trap Diplomacy Narrative: An Empirical Analysis
- A Social Constructionist Approach to Institutional Change: The Case of the Romanian Competition Council
- Conscription Reloaded? The Debate About Compulsory Service in Germany in 2022 and the Peoples’ Attitudes Towards It
- Always a Bridesmaid: A Machine Learning Approach to Minor Party Identity in Multi-Party Systems
- Commentary and Responses
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Artikel in diesem Heft
- Frontmatter
- Articles
- Tweedie Regression Analysis of Determinants of Birth Weight in Navrongo
- The Chinese Debt Trap Diplomacy Narrative: An Empirical Analysis
- A Social Constructionist Approach to Institutional Change: The Case of the Romanian Competition Council
- Conscription Reloaded? The Debate About Compulsory Service in Germany in 2022 and the Peoples’ Attitudes Towards It
- Always a Bridesmaid: A Machine Learning Approach to Minor Party Identity in Multi-Party Systems
- Commentary and Responses
- The Nexus between Federal Revenue and Spending in Canada: A Time-Frequency Perspective
