The reactions that science triggers on the people it studies, describes, or theorises about, can affect the science itself and its claims to knowledge. This phenomenon, which we call reactivity, has been discussed in many different areas of the social sciences and the philosophy of science, falling under different rubrics such as the Hawthorne effect, self-fulfilling prophecies, the looping effects of human kinds, the performativity of models, observer effects, experimenter effects and experimenter demand effects. In this paper we review state-of-the-art (...) research that falls under the remit of the philosophy of reactivity by considering ontological, epistemic and moral issues that reactivity raises. Along the way, we devote special attention to articles belonging to this journal's Topical Collection entitled “Reactivity in the Human Sciences”. (shrink)

Reactivity in qualitative data collection occurs when a researcher generates data about a situation with reactivity, that is, a situation in which the ongoing research affects the research participants such that they, say, diverge from their routines when the researcher is present, or tell the researcher what they think she wants to hear. In qualitative research, there are two basic approaches to reactivity. The traditional position maintains that data should ideally be collected in situations without any reactivity. In other words, (...) good data are reactivity free. By contrast, the more recent view holds that data from situations with reactivity are fine as long as the researcher is aware of the occurring reactivity so that she can take it into account when interpreting her data. In this fashion, good data are reactivity transparent. In this paper, I first spell out and defend the more recent approach to reactivity. I argue that qualitative data are reactivity transparent when conjoined with true reactivity assumptions and that, thus supplemented, data are informative about social life independently of its being studied. Next, I examine various issues raised by the requirement to put forth true reactivity assumptions. Lastly, I use my discussion of reactivity transparency as a basis for providing a framework for thinking about good qualitative data. (shrink)

The validity of psychological measurement is crucially connected to a peculiar form of epistemic circularity. This circularity can be a threat when there are no independent ways to assess whether a certain procedure is actually measuring the intended target of measurement. This paper focuses on how Gustav Theodor Fechner addressed the measurement circularity that emerged in his psychophysical research. First, I show that Fechner's approach to the problem of circular measurement involved a core idealizing assumption of a shared human physiology. (...) Second, I assess Fechner's approach to this issue against the backdrop of his own epistemology of measurement and the measurement context of his time. Third, I claim that, from a coherentist and historicallysituated perspective, Fechner's quantification can be regarded as a first successful step of a longer-term quantification process. To conclude, I draw from these insights some general epistemological reflections that are relevant to current quantitative psychology. (shrink)

This commentary analyzes the extent to which the incommensurability problem can be resolved through the proposed alternative method of integrative experiment design. We suggest that, although one aspect of incommensurability is successfully addressed (dimensional incommensurability), the proposed design space method does not yet alleviate another major source of discontinuity, which we call conceptual incommensurability.

Scientists aim to remediate artifacts in their experimental datasets. However, the remediation of one artifact can result in another. Why might this happen, and what does this consequence tell us about how we should account for artifacts and their control? In this paper, I explore a case in functional neuroimaging where remediation appears to have caused this problem. I argue that remediation amounts to a change to an experimental arrangement. These changes need not be surgical, and the arrangement need not (...) satisfy the criterion of causal modularity. Thus, remediation can affect more than just the factor responsible for the artifact. However, if researchers can determine the consequences of their remediation, they can make adjustments that control for the present artifact as well as for previously controlled ones. Current philosophical accounts of artifacts and the factors responsible for them cannot adequately address this issue, as they do not account for what is needed for artifact remediation (and specifically correction). I support my argument by paralleling it with ongoing concerns regarding the transparency of complex computational systems, as near future remediation across the experimental life sciences will likely make greater use of AI tools to correct for artifacts. (shrink)

Although researchers agree on the importance of validity, they have not yet reached a consensus on what validity consists of. This article traces the historic trajectories of validity theory development in three research traditions: psychometrics, experiment in social settings, and animal models of psychiatric disorders, showing that the multiplicity in the concept of validity is shaped by its multiple historic trajectories and reflects the diversity of practices and concerns in different research traditions. I argue that specifying validity of what target (...) practice and for what purpose in discussions helps to connect validity to its rich context that gives rise to its specific meaning and relevance. (shrink)