Observability and Abstraction: Two Challenges for the Adoption of Scientific Realism in Philosophy of Social Sciences
Abstract Traditionally, scientific realism (the view that sciences’ success depends on the truth of their contents), implies the distinction between observable and unobservable entities. However, when we see the social sciences, it seems to be that this distinction is untenable. Does it mean that scientific realism is unsustainable for social sciences? In this paper, I defend the idea that scientific realism is a possible approach in philosophy of social sciences, but in a different way than the traditional account. When we analyze social sciences, we see that scientific realism can dispense with the observable/unobservable distinction, and in turn, we need to focus the debate on relation to the assumptions behind generation of explanations, especially in the case of causal explanations. The main implication of this view is that, in the case of social sciences, the support of scientific realism is not at the level of ontological commitments, but instead in the methodological commitments that guide research design.
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Asay, Jamin (2019). Going local: A defense of methodological localism about scientific realism. Synthese, 196(2), 587–609. DOI: 10.1007/s11229-016-1072-6
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Chakravartty, Anjan (2008). What you don’t know can’t hurt you: Realism and the unconceived. Philosophical Studies, 137(1), 149–158. DOI: 10.1007/s11098-007-9173-1
Duhem, Pierre (1954). The Aim and Structure of Physical Theory. Princeton: Princeton University Press.
Esser, Hartmut (1996). What Is Wrong with «Variable Sociology»? European Sociological Review, 12(2), 159–166. Obtenido de https://www.jstor.org/stable/522433
Glennan, Stuart (2002). Rethinking Mechanistic Explanation. Philosophy of Science, 69(S3), 342–353. DOI: 10.1086/341857
Glennan, Stuart, Illari, Phyllis y Weber, Erik (2022). Six Theses on Mechanisms and Mechanistic Science. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie, 53(2), 143–161. DOI: 10.1007/s10838-021-09587-x
Goldthorpe, John (2001). Causation, Statistics, and Sociology. European Sociological Review, 17(1), 1–20. DOI: 10.1093/esr/17.1.1
Goldthorpe, John (2016). Sociology as a Population Science. Cambridge University Press.
Gonzalez, Wenceslao (2020). Novelty in Scientific Realism: New Approaches to an Ongoing Debate. En W. J. Gonzalez (Ed.), New Approaches to Scientific Realism (pp. 1–24). De Gruyter. DOI: 10.1515/9783110664737-001
Harp, Randall y Khalifa, Kareem (2017). Realism and Antirealism. En L. McIntyre & A. Rosenberg (Eds.), The Routledge Companion to Philosophy of Social Science (pp. 254–269). Routledge.
Hausman, Daniel (1998). Problems with Realism in Economics. Economics and Philosophy, 14(2), 185–213. DOI: 10.1017/S0266267100003837
Hedström, Peter (2005). Dissecting the Social: On the Principles of Analytical Sociology. Cambridge University Press.
Hedström, Peter y Ylikoski, Petri (2010). Causal Mechanisms in the Social Sciences. Annual Review of Sociology, 36(1), 49–67. DOI: 10.1146/annurev.soc.012809.102632
Holland, Paul (1986). Statistics and Causal Inference. Journal of the American Statistical Association, 81(396), 945–960. DOI: 10.2307/2289064
King, Gary, Keohane, Robert y Verba, Sidney (1994). Designing social inquiry: Scientific inference in qualitative research. Princeton University Press.
Kish, Leslie (2004). Statistical design for research (Wiley classics library ed). Wiley Interscience.
Knight, Carly y Winship, Christopher (2013). The causal implications of mechanistic thinking: Identification using directed acyclic graphs (DAGs). En S. L. Morgan (Ed.), Handbook of Causal Analysis for Social Research (pp. 275–300). Springer Netherlands.
Kuipers, Teo (2020). Stratified Nomic Realism. En W. J. Gonzalez (Ed.), New Approaches to Scientific Realism (pp. 145–166). De Gruyter. DOI: 10.1515/9783110664737-008
Laudan, Larry (1981). A confutation of convergent realism. Philosophy of Science, 48(1), 19–49. DOI: 10.1086/288975
Lawler, Insa (2021). Scientific Understanding and Felicitous Legitimate Falsehoods. Synthese, 198(7), 6859–6887. DOI: 10.1007/s11229-019-02495-0
Lewens, Tim (2016). The Meaning of Science: An Introduction to the Philosophy of Science. Basic Books.
Lipton, Peter (2004). Inference to the Best Explanation (2nd ed.). Routledge.
Little, Daniel (2020). A New Social Ontology of Government: Consent, Coordination, and Authority (1st ed.). Springer International Publishing; Palgrave Pivot.
Machamer, Peter, Darden, Lindley y Craver, Carl (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25. Obtenido de http://www.jstor.org/stable/188611
Magnus, P. D. y Callender, Craig (2004). Realist ennui and the base rate fallacy. Philosophy of Science, 71(3), 320–338. DOI: 10.1086/421536
Mäki, Uskali (2005). Reglobalizing Realism by Going Local, or (How) Should Our Formulations of Scientific Realism be Informed about the Sciences? Erkenntnis, 63(2), 231–251. DOI: 10.1007/s10670-005-3227-6
Mäki, Uskali (2009). Realistic Realism about Unrealistic Models. The Oxford Handbook of Philosophy of Economics. DOI: 10.1093/oxfordhb/9780195189254.003.0004
Mäki, Uskali (2011). Scientific realism as a challenge to economics (and vice versa). Journal of Economic Methodology, 18(01), 1–12. DOI: 10.1080/1350178X.2011.553372
Marchionni, C. y Reijula, S. (2019). What is Mechanistic Evidence, and Why Do We Need It for Evidence-Based Policy? Studies in History and Philosophy of Science Part A, 73, 54–63. DOI: 10.1016/j.shpsa.2018.08.003
Maurer, Andrea (2016). Social Mechanisms as Special Cases of Explanatory Sociology: Notes toward Systemizing and Expanding Mechanism-based Explanation within Sociology. Analyse & Kritik, 38(1), 31–52. DOI: 10.1515/auk-2016-0103
Morgan, Stephen. y Winship, Christopher (2014). Counterfactuals and Causal Inference. Methods and Principles for Social Research. Cambridge University Press.
OECD (2019). Under pressure: The squeezed middle class (p. 173). DOI: 10.1787/689afed1-en
Psillos, Stathis (1999). Scientific Realism: How Science Tracks Truth. Routledge.
Psillos, Stathis (2017). The realist turn in the philosophy of science. En J. Saatsi (Ed.), The routledge handbook of scientific realism (pp. 20–34). Routledge.
Reiss, Julien (2012). The explanation paradox. Journal of Economic Methodology, 19(1), 43–62. DOI: 10.1080/1350178X.2012.661069
Rowbottom, Darrel (2019). Scientific realism: What it is, the contemporary debate, and new directions. Synthese, 196(2), 451–484. DOI: 10.1007/s11229-017-1484-y
Rubin, Donald (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701. DOI: 10.1037/h0037350
Russo, F., Wunsch, G. y Mouchart, M. (2011). Inferring Causality through Counterfactuals in Observational Studies—Some Epistemological Issues. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 111(1), 43–64. DOI: 10.1177/0759106311408891
Saatsi, Juha (2017). The routledge handbook of scientific realism (J. Saatsi, Ed.). Routledge.
Stanford, Kyle (2003). Pyrrhic Victories for Scientific Realism. Journal of Philosophy, 100(11), 553–572. Obtenido de https://www.jstor.org/stable/3655744
Stanford, Kyle (2006). Exceeding Our Grasp: Science, History, and the Problem of Unconceived Alternatives. Oxford University Press.
Stanford, Kyle (2017). Unconceived Alternatives and the Strategy of Historical Ostension. En J. Saatsi (Ed.), The routledge handbook of scientific realism (pp. 212–224). Routledge.
Steel, Daniel (2004). Social mechanisms and causal inference. Philosophy of the Social Sciences, 34(1), 55–78. DOI: 10.1177/0048393103260775
Sugden, Robert (2013). How fictional accounts can explain. Journal of Economic Methodology, 20(3), 237–243. DOI: 10.1080/1350178X.2013.828872
Sullivan, Eric y Khalifa, Kareem (2019). Idealizations and Understanding: Much Ado About Nothing? Australasian Journal of Philosophy, 97(4), 673–689. DOI: 10.1080/00048402.2018.1564337
Trout, John (1998). Measuring the intentional world: Realism, naturalism, and quantitative methods in the behavioral sciences. Oxford University Press.
Woodward, James (2015). Methodology, Ontology, and Interventionism. Synthese, 192(11), 3577–3599. DOI: 10.1007/s11229-014-0479-1
Worrall, John (1989). Structural Realism: The Best of Both Worlds? Dialectica, 43(1-2), 99–124. DOI: 10.1111/j.1746-8361.1989.tb00933.x
Ylikoski, Petri (2018). Social Mechanisms. En S. Glennan & P. M. Illari (Eds.), The Routledge handbook of mechanisms and mechanical philosophy (pp. 401–412). Routledge.
Asay, Jamin (2019). Going local: A defense of methodological localism about scientific realism. Synthese, 196(2), 587–609. DOI: 10.1007/s11229-016-1072-6
Bechtel, William y Abrahamsen, Adele (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441. DOI: 10.1016/j.shpsc.2005.03.010
Bouwel, Jeroen. Van (2014). Explanatory Strategies Beyond The Individualism/Holism Debate. En J. Zahle & F. Collin (Eds.), Rethinking the Individualism-Holism Debate (pp. 153–175). Springer.
Boyd, Richard (1980). Scientific Realism and Naturalistic Epistemology. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1980, 613–662.
CEPAL (2021). Clases medias en tiempos de crisis: Vulnerabilidad persistente, desafíos para la cohesión y un nuevo pacto social en Chile. CEPAL. Obtenido de https://www.cepal.org/es/publicaciones/47184-clases-medias-tiempos-crisis-vulnerabilidad-persistente-desafios-la-cohesion-un
Chakravartty, Anjan (2007). A Metaphysics for Scientific Realism: Knowing the Unobservable. Cambridge University Press.
Chakravartty, Anjan (2008). What you don’t know can’t hurt you: Realism and the unconceived. Philosophical Studies, 137(1), 149–158. DOI: 10.1007/s11098-007-9173-1
Duhem, Pierre (1954). The Aim and Structure of Physical Theory. Princeton: Princeton University Press.
Esser, Hartmut (1996). What Is Wrong with «Variable Sociology»? European Sociological Review, 12(2), 159–166. Obtenido de https://www.jstor.org/stable/522433
Glennan, Stuart (2002). Rethinking Mechanistic Explanation. Philosophy of Science, 69(S3), 342–353. DOI: 10.1086/341857
Glennan, Stuart, Illari, Phyllis y Weber, Erik (2022). Six Theses on Mechanisms and Mechanistic Science. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie, 53(2), 143–161. DOI: 10.1007/s10838-021-09587-x
Goldthorpe, John (2001). Causation, Statistics, and Sociology. European Sociological Review, 17(1), 1–20. DOI: 10.1093/esr/17.1.1
Goldthorpe, John (2016). Sociology as a Population Science. Cambridge University Press.
Gonzalez, Wenceslao (2020). Novelty in Scientific Realism: New Approaches to an Ongoing Debate. En W. J. Gonzalez (Ed.), New Approaches to Scientific Realism (pp. 1–24). De Gruyter. DOI: 10.1515/9783110664737-001
Harp, Randall y Khalifa, Kareem (2017). Realism and Antirealism. En L. McIntyre & A. Rosenberg (Eds.), The Routledge Companion to Philosophy of Social Science (pp. 254–269). Routledge.
Hausman, Daniel (1998). Problems with Realism in Economics. Economics and Philosophy, 14(2), 185–213. DOI: 10.1017/S0266267100003837
Hedström, Peter (2005). Dissecting the Social: On the Principles of Analytical Sociology. Cambridge University Press.
Hedström, Peter y Ylikoski, Petri (2010). Causal Mechanisms in the Social Sciences. Annual Review of Sociology, 36(1), 49–67. DOI: 10.1146/annurev.soc.012809.102632
Holland, Paul (1986). Statistics and Causal Inference. Journal of the American Statistical Association, 81(396), 945–960. DOI: 10.2307/2289064
King, Gary, Keohane, Robert y Verba, Sidney (1994). Designing social inquiry: Scientific inference in qualitative research. Princeton University Press.
Kish, Leslie (2004). Statistical design for research (Wiley classics library ed). Wiley Interscience.
Knight, Carly y Winship, Christopher (2013). The causal implications of mechanistic thinking: Identification using directed acyclic graphs (DAGs). En S. L. Morgan (Ed.), Handbook of Causal Analysis for Social Research (pp. 275–300). Springer Netherlands.
Kuipers, Teo (2020). Stratified Nomic Realism. En W. J. Gonzalez (Ed.), New Approaches to Scientific Realism (pp. 145–166). De Gruyter. DOI: 10.1515/9783110664737-008
Laudan, Larry (1981). A confutation of convergent realism. Philosophy of Science, 48(1), 19–49. DOI: 10.1086/288975
Lawler, Insa (2021). Scientific Understanding and Felicitous Legitimate Falsehoods. Synthese, 198(7), 6859–6887. DOI: 10.1007/s11229-019-02495-0
Lewens, Tim (2016). The Meaning of Science: An Introduction to the Philosophy of Science. Basic Books.
Lipton, Peter (2004). Inference to the Best Explanation (2nd ed.). Routledge.
Little, Daniel (2020). A New Social Ontology of Government: Consent, Coordination, and Authority (1st ed.). Springer International Publishing; Palgrave Pivot.
Machamer, Peter, Darden, Lindley y Craver, Carl (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25. Obtenido de http://www.jstor.org/stable/188611
Magnus, P. D. y Callender, Craig (2004). Realist ennui and the base rate fallacy. Philosophy of Science, 71(3), 320–338. DOI: 10.1086/421536
Mäki, Uskali (2005). Reglobalizing Realism by Going Local, or (How) Should Our Formulations of Scientific Realism be Informed about the Sciences? Erkenntnis, 63(2), 231–251. DOI: 10.1007/s10670-005-3227-6
Mäki, Uskali (2009). Realistic Realism about Unrealistic Models. The Oxford Handbook of Philosophy of Economics. DOI: 10.1093/oxfordhb/9780195189254.003.0004
Mäki, Uskali (2011). Scientific realism as a challenge to economics (and vice versa). Journal of Economic Methodology, 18(01), 1–12. DOI: 10.1080/1350178X.2011.553372
Marchionni, C. y Reijula, S. (2019). What is Mechanistic Evidence, and Why Do We Need It for Evidence-Based Policy? Studies in History and Philosophy of Science Part A, 73, 54–63. DOI: 10.1016/j.shpsa.2018.08.003
Maurer, Andrea (2016). Social Mechanisms as Special Cases of Explanatory Sociology: Notes toward Systemizing and Expanding Mechanism-based Explanation within Sociology. Analyse & Kritik, 38(1), 31–52. DOI: 10.1515/auk-2016-0103
Morgan, Stephen. y Winship, Christopher (2014). Counterfactuals and Causal Inference. Methods and Principles for Social Research. Cambridge University Press.
OECD (2019). Under pressure: The squeezed middle class (p. 173). DOI: 10.1787/689afed1-en
Psillos, Stathis (1999). Scientific Realism: How Science Tracks Truth. Routledge.
Psillos, Stathis (2017). The realist turn in the philosophy of science. En J. Saatsi (Ed.), The routledge handbook of scientific realism (pp. 20–34). Routledge.
Reiss, Julien (2012). The explanation paradox. Journal of Economic Methodology, 19(1), 43–62. DOI: 10.1080/1350178X.2012.661069
Rowbottom, Darrel (2019). Scientific realism: What it is, the contemporary debate, and new directions. Synthese, 196(2), 451–484. DOI: 10.1007/s11229-017-1484-y
Rubin, Donald (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701. DOI: 10.1037/h0037350
Russo, F., Wunsch, G. y Mouchart, M. (2011). Inferring Causality through Counterfactuals in Observational Studies—Some Epistemological Issues. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 111(1), 43–64. DOI: 10.1177/0759106311408891
Saatsi, Juha (2017). The routledge handbook of scientific realism (J. Saatsi, Ed.). Routledge.
Stanford, Kyle (2003). Pyrrhic Victories for Scientific Realism. Journal of Philosophy, 100(11), 553–572. Obtenido de https://www.jstor.org/stable/3655744
Stanford, Kyle (2006). Exceeding Our Grasp: Science, History, and the Problem of Unconceived Alternatives. Oxford University Press.
Stanford, Kyle (2017). Unconceived Alternatives and the Strategy of Historical Ostension. En J. Saatsi (Ed.), The routledge handbook of scientific realism (pp. 212–224). Routledge.
Steel, Daniel (2004). Social mechanisms and causal inference. Philosophy of the Social Sciences, 34(1), 55–78. DOI: 10.1177/0048393103260775
Sugden, Robert (2013). How fictional accounts can explain. Journal of Economic Methodology, 20(3), 237–243. DOI: 10.1080/1350178X.2013.828872
Sullivan, Eric y Khalifa, Kareem (2019). Idealizations and Understanding: Much Ado About Nothing? Australasian Journal of Philosophy, 97(4), 673–689. DOI: 10.1080/00048402.2018.1564337
Trout, John (1998). Measuring the intentional world: Realism, naturalism, and quantitative methods in the behavioral sciences. Oxford University Press.
Woodward, James (2015). Methodology, Ontology, and Interventionism. Synthese, 192(11), 3577–3599. DOI: 10.1007/s11229-014-0479-1
Worrall, John (1989). Structural Realism: The Best of Both Worlds? Dialectica, 43(1-2), 99–124. DOI: 10.1111/j.1746-8361.1989.tb00933.x
Ylikoski, Petri (2018). Social Mechanisms. En S. Glennan & P. M. Illari (Eds.), The Routledge handbook of mechanisms and mechanical philosophy (pp. 401–412). Routledge.
Armijo Torres, Álvaro. (2023). Observability and Abstraction: Two Challenges for the Adoption of Scientific Realism in Philosophy of Social Sciences. ArtefaCToS. Revista De Estudios Sobre La Ciencia Y La tecnología, 12(2), 5–31. https://doi.org/10.14201/art2023.31135
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