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#mixedmethods

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We are excited about tomorrow's keynote by Jill Walker Rettberg, talking about "Qualitative methods for analysing generative AI: Experiences with machine vision and AI storytelling".
The keynote is part of our Mixed Methods Winter School on “AI Methods: From Probing to Prompting”, which centers on the implications of AI methods for new forms of sense-making and human-machine co-creation.
👉 programme: lnkd.in/gVjHKYsM
#mixedmethods #AI #digitalmethods #probing #prompting

Resolving empirical controversies with mechanistic evidence | Synthese
link.springer.com/article/10.1 #PhilSci
Disclaimer for starters: This is not meant to be a disciplinary beauty contest.
I fully agree with
- the argument that evidence about mechanisms can resolve statistical disagrements
1/ #PhilosophyOfScience #MixedMethods

SpringerLinkResolving empirical controversies with mechanistic evidence - SyntheseThe results of econometric modeling are fragile in the sense that minor changes in estimation techniques or sample can lead to statistical models that support inconsistent causal hypotheses. The fragility of econometric results undermines making conclusive inferences from the empirical literature. I argue that the program of evidential pluralism, which originated in the context of medicine and encapsulates to the normative reading of the Russo-Williamson Thesis that causal claims need the support of both difference-making and mechanistic evidence, offers a ground for resolving empirical disagreements. I analyze a recent econometric controversy regarding the tax elasticity of cigarette consumption and smoking intensity. Both studies apply plausible estimation techniques but report inconsistent results. I show that mechanistic evidence allows for discriminating econometric models representing genuine causal relations from accidental dependencies in data. Furthermore, I discuss the differences between biological and social mechanisms and mechanistic evidence across the disciplines. I show that economists mainly rely on mathematical models to represent possible mechanisms (i.e., mechanisms that could produce a phenomenon of interest). Still, claiming the actuality of the represented mechanisms requires establishing that crucial assumptions of these models are descriptively adequate. I exemplify my approach to assessing the quality of mechanistic evidence in economics with an analysis of two models of rational addiction.

Lots of gems in this #mixedMethods preprint! Ranging from techniques for connecting nested data sources at different scales, to comparing individuals' reported actions with their actual behaviors, and even tricks for eliciting strong taste judgments during #qualitative interviews.
**[Integrating digital traces into mixed methods designs. An application to the study of online music listening using survey, interview & stream history data collected from the same people**](osf.io/preprints/socarxiv/ynm6)

Terminology and #MixedMethods Research: A Persistent Challenge journals.sagepub.com/doi/full/ Among other things, "mixed methods" is preferred over "multimethod". Argument is that multimethod research could be quant-quant or qual-qual combination, mixed methods are qual-quant. This may be a "potato, potato" thing, but I like the editorial clarifies this. In my MMR courses, I usually say the two are different w/o having a strong basis for my claim.

Time for re-introduction?

I'm Nadav Perez-Vaisvidovsky, senior lecturer at the faculty of #socialwork, #ashkelon academic college #aac, currently visiting at #UCL #TCRU

My research interests are at the intersections of #Fatherhood and the #welfarestate - specifically I'm currently engaged in projects in two fields: #ParentalLeave for #fathers and the interaction of fathers with the #welfare and #childprotection systems. Mostly #qualitative methods but also #mixedmethods