The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Peter Monnerjahn - One of the best experts on this subject based on the ideXlab platform.
-
Falsificationism is not just ‘potential’ Falsifiability, but requires ‘actual’ falsification: Social psychology, critical rationalism, and progress in science
Journal for the Theory of Social Behaviour, 2017Co-Authors: Peter Holtz, Peter MonnerjahnAbstract:Based on an analysis of ten popular introductions to social psychology, we will show that Karl Popper's philosophy of ‘critical rationalism’ so far has had little to no traceable influence on the epistemology and practice of social psychology. If Popper is quoted or mentioned in the textbooks at all, the guiding principle of ‘falsificationism’ is reduced to a mere ‘Falsifiability’ and some central elements of critical rationalism are left out – those that are incompatible with positivism and inductivism. Echoing earlier attempts to introduce Popper to social psychology by Paul Meehl and Tom Pettigrew, we will argue that a discussing Popper's ideas in more depth could help social psychology to move forward in view of the ‘crisis of confidence’ (Pashler and Wagenmakers, 2012) that has emerged recently in view of the ‘Stapel affair’ and the reports of failures to replicate social psychological experiments in high-powered replication attempts.
Marco Viceconti - One of the best experts on this subject based on the ideXlab platform.
-
a tentative taxonomy for predictive models in relation to their Falsifiability
Philosophical Transactions of the Royal Society A, 2011Co-Authors: Marco VicecontiAbstract:The growing importance of predictive models in biomedical research raises some concerns on the correct methodological approach to the falsification of such models, as they are developed in interdis...
V Debrunner - One of the best experts on this subject based on the ideXlab platform.
-
using parameter sensitivity and interdependence to predict model scope and Falsifiability
Journal of Experimental Psychology: General, 1996Co-Authors: Stephan Lewandowsky, V DebrunnerAbstract:One important criterion for a model's utility is its scope, the ability to predict a wide range of results. Scope is often difficult to ascertain without extensive data fitting. For example, J. E. Cutting, N. Bruno, N. P. Brady, and C. Moore (1992) compared 2 models of perceived visual depth by fitting many data sets that were arbitrarily generated from underlying functions. They then defined scope as the number of functions a model could account for. We present an alternative technique for scope evaluation that is based on analysis of the behavior of a model's parameters and does not require extensive data fitting. The technique examines the ratio between the overall interdependence among model parameters and their sensitivity, which we show to be inversely related to a model's scope.
Martin Bojowald - One of the best experts on this subject based on the ideXlab platform.
-
loop quantum cosmology space time structure and Falsifiability
Lecture Notes in Physics, 2013Co-Authors: Martin BojowaldAbstract:Loop quantum cosmology attempts to understand the full dynamics of loop quantum gravity by realizing crucial effects in simpler, usually symmetric settings. Several subtleties arise especially when cosmological questions are to be addressed, related to possible mini-superspace artefacts, consistent cosmological perturbation theory, and quantum space-time structure. Recent work on inhomogeneous perturbations has highlighted some of the dangers of an over-reliance on simple models, sometimes not just reduced by symmetry but also in the possible forms of matter or quantum corrections. Only a consistent treatment of inhomogeneity, taking into account the full gauge structure related to general covariance, can show what happens at high densities in quantum gravity. The relevant methods and results (especially effective equations, potential observational signatures, singularity resolution and signature change) are surveyed in here.
Moritz Heene - One of the best experts on this subject based on the ideXlab platform.
-
additive conjoint measurement and the resistance toward Falsifiability in psychology
Frontiers in Psychology, 2013Co-Authors: Moritz HeeneAbstract:The history of the past four decades of the theory and application of additive conjoint measurement (ACM) is characterized by vivid developments of its theoretical foundation (cf. Luce and Tukey, 1964; Krantz et al., 1971, 2006; Narens, 1974), industrious developments of statistical and computational implementations (cf. Karabatsos and Ullrich, 2002; Karabatsos and Sheu, 2004; Karabatsos, 2005; Myung et al., 2005) and heated debates about its applicability and significance in psychology (cf. Michell, 1997, 2009; Borsboom and Mellenbergh, 2004; Barrett, 2008; Borsboom and Scholten, 2008; Kyngdon, 2008a; Trendler, 2009). What started as a promising foundation to solve the everlasting debate about the quantitative nature of psychological attributes (Ferguson et al., 1939) ended in perseverative debates with very little transfer to mainstream psychological science still being dominated by structural equation modeling (SEM) and item response theory (IRT). After reading the aforementioned articles, and comparing their implications with the day-to-day business of mainstream psychological science, even an unbiased reader would certainly agree with Cliff (1992) that ACM was a “… revolution that never happened” (p. 186). It is not the aim of this article, to discredit the efforts of mathematical psychology and proponents of ACM in particular. I just want to address the naive but relevant question why ACM as a stringent way to formalize and to test the requirements of quantitative measurement in psychology has not been embraced by mainstream psychology as a means to an end to test what they always claim: that most of the attributes (e.g., intelligence and personality factors) are quantitative. An attribute possessing a quantitative structure is required to satisfy the three conditions of ordinality (transitivity, antisymmetry, and strong connexity) and the six conditions of additivity (associativity, commutativity, monotonicity, solvability, positivity, and the Archimedean condition; cf. Michell, 1990, p. 52f.). Most of these conditions are testable hypotheses but I have never seen any empirical test in psychological articles before data were analyzed with SEM or IRT models, which already assume the quantitative structure of the attributes under consideration as argued below. Somewhere during my psychology studies at the university I learned that psychology is an empirical science and that there is therefore no room for claims that should just be believed. However, given the assumed but almost never tested quantitative nature of most of the psychological attributes as reflected in factor analysis, SEM and IRT models, I must have missed or misunderstood something.