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Alan Sokal writes: We know perfectly well that our politicians (or at least some of them) lie to us; we take it for granted; we are inured to it. And that may be precisely the problem. Perhaps we have become so inured to political lies — so hard-headedly cynical — that we have lost our […]
The post Sokal: “science is not merely a bag of clever tricks . . . Rather, the natural sciences are nothing more or less than one particular application — albeit an unusually
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All this discussion of plagiarism is leaving a bad taste in my mouth (or, I guess I should say, a bad feeling in my fingers, given that I’m expressing all this on the keyboard) so I wanted to close off the workweek with something more interesting. I happened to come across the above-titled paper by […]
The post The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Basbøll has another post regarding some copying-without-attribution by the somewhat-famous academic entertainer Slavoj Zizek. In his post, Basbøll links to theologian and professor Adam Kotsko (cool: who knew there were still theologians out and about in academia?) who defends Zizek, in part on the grounds that Zizek’s critics were being too harsh. Kotsko writes of […]
The post Defense by escalation appeared first on Statistical Modeling, Causal Inference, and Social
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Boolean models (“it’s either A or (B and C)”) seem to be the natural way that we think, but additive models (“10 points if you have A, 3 points if you have B, 2 points if you have C”) seem to describe reality better—at least, the aspects of reality that I study in my research. […]
The post Message to Booleans: It’s an additive world, we just live in it appeared first on Statistical Modeling, Causal Inference, and Social Science.

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(scheduled to appear in a few months, of course). I think you’ll like it. Or hate it. Depending on who you are.
The post Hey, I just wrote my April Fool’s post! appeared first on Statistical Modeling, Causal Inference, and Social Science.