43 research outputs found
Is Quantitative Research Ethical? Tools for Ethically Practicing, Evaluating, and Using Quantitative Research
This editorial offers new ways to ethically practice, evaluate, and use quantitative research (QR). Our central claim is that ready-made formulas for QR, including 'best practices' and common notions of 'validity' or 'objectivity,' are often divorced from the ethical and practical implications of doing, evaluating, and using QR for specific purposes. To focus on these implications, we critique common theoretical foundations for QR and then recommend approaches to QR that are 'built for purpose,' by which we mean designed to ethically address specific problems or situations on terms that are contextually relevant. For this, we propose a new tool for evaluating the quality of QR, which we call 'relational validity.' Studies, including their methods and results, are relationally valid when they ethically connect researchers' purposes with the way that QR is oriented and the ways that it is done—including the concepts and units of analysis invoked, as well as what its 'methods' imply more generally. This new way of doing QR can provide the liberty required to address serious worldly problems on terms that are both practical and ethically informed in relation to the problems themselves rather than the confines of existing QR logics and practices.cited By
Carnival and Spectacle in Krewe de Vieux and the Mystic Krewe of Spermes: The Mingling o Organization and Celebration
Investigating the Effects of Moral Disengagement and Participation on Unethical Work Behavior
From Data to Causes III: Bayesian Priors for General Cross-Lagged Panel Models (GCLM)
This article describes some potential uses of Bayesian estimation for time-series and panel data models by incorporating information from prior probabilities (i.e., priors) in addition to observed data. Drawing on econometrics and other literatures we illustrate the use of informative “shrinkage” or “small variance” priors (including so-called “Minnesota priors”) while extending prior work on the general cross-lagged panel model (GCLM). Using a panel dataset of national income and subjective well-being (SWB) we describe three key benefits of these priors. First, they shrink parameter estimates toward zero or toward each other for time-varying parameters, which lends additional support for an income → SWB effect that is not supported with maximum likelihood (ML). This is useful because, second, these priors increase model parsimony and the stability of estimates (keeping them within more reasonable bounds) and thus improve out-of-sample predictions and interpretability, which means estimated effect should also be more trustworthy than under ML. Third, these priors allow estimating otherwise under-identified models under ML, allowing higher-order lagged effects and time-varying parameters that are otherwise impossible to estimate using observed data alone. In conclusion we note some of the responsibilities that come with the use of priors which, departing from typical commentaries on their scientific applications, we describe as involving reflection on how best to apply modeling tools to address matters of worldly concern
The Role of Dreams in the Evolution of the Human Mind
This paper presents an evolutionary argument for the role of dreams in the development of human cognitive processes. While a theory by Revonsuo (2000) proposes that dreams allow for threat rehearsal and therefore provide an evolutionary advantage, the goal of this paper is to extend this argument by commenting on other fitness-enhancing aspects of dreams. Rather than a simple threat rehearsal mechanism, it is argued that dreams reflect a more general virtual rehearsal mechanism that is likely to play an important role in the development of human cognitive capacities. This paper draws on current work in cognitive neuroscience and philosophy of mind in developing the argument