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  1. Understanding society: an interview with Daniel Little.Daniel Little & Jamie Morgan - 2022 - Journal of Critical Realism 22 (2):293-345.
    In this interview, Daniel Little provides an overview of his life and work in academia. Among other things, he discusses an actor-centred approach to theory of social ontology. For Little, this approach complements the assumptions of critical realism, in that it accords full ontological importance to social structures, causal mechanisms, and enduring and influential normative systems. The approach casts doubt, however, on the idea of ‘strong emergence' of social structures, the idea that social structures have properties and causal powers that (...)
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  • Przyczyna i Wyjaśnianie: Studium Z Filozofii i Metodologii Nauk.Paweł Kawalec - 2006 - Lublin: Wydawnictwo KUL.
    Przedmowa Problematyka związana z zależnościami przyczynowymi, ich modelowaniem i odkrywa¬niem, po długiej nieobecności w filozofii i metodologii nauk, budzi współcześnie duże zainteresowanie. Wiąże się to przede wszystkim z dynamicznym rozwojem, zwłaszcza od lat 1990., technik obli¬czeniowych. Wypracowane w tym czasie sieci bayesowskie uznaje się za matematyczny język przyczynowości. Pozwalają one na daleko idącą auto¬matyzację wnioskowań, co jest także zachętą do podjęcia prób algorytmiza¬cji odkrywania przyczyn. Na potrzeby badań naukowych, które pozwalają na przeprowadzenie eksperymentu z randomizacją, standardowe metody ustalania zależności przyczynowych (...)
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  • Interventionism and Over-Time Causal Analysis in Social Sciences.Tung-Ying Wu - 2022 - Philosophy of the Social Sciences 52 (1-2):3-24.
    The interventionist theory of causation has been advertised as an empirically informed and more nuanced approach to causality than the competing theories. However, previous literature has not yet analyzed the regression discontinuity (hereafter, RD) and the difference-in-differences (hereafter, DD) within an interventionist framework. In this paper, I point out several drawbacks of using the interventionist methodology for justifying the DD and RD designs. However, I argue that the first step towards enhancing our understanding of the DD and RD designs from (...)
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  • Social mechanisms and causal inference.Daniel Steel - 2004 - Philosophy of the Social Sciences 34 (1):55-78.
    Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the account is (...)
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  • Using case studies in the social sciences: methods, inferences, purposes.Attilia Ruzzene - 2015 - Erasmus Journal for Philosophy and Economics 8 (1):123.
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  • What Can Mechanisms Do for You? Mechanisms and the Problem of Confounders in the Social Sciences.María Jiménez-Buedo & Juan Carlos Squitieri - 2019 - Philosophy of the Social Sciences 49 (3):210-231.
    The idea that mechanisms are crucially important to differentiate between genuine and spurious causal relations is ubiquitous both in the philosophical and in the social scientific literature. Yet...
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  • Causality and causal modelling in the social sciences.Federica Russo - 2009 - Springer, Dordrecht.
    The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant (...)
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