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I’d like to see a global version of this, and with inclusion of more complex weighting than just 10% outliers. You want to weight “freak” events more. And I’d like to see a broader extremes index measured in terms other than dollars. Notice the “billion dollar weather” reporting
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In general,I’m not a natural quant, and I trust stories more than I trust naive data, or worse, unacknowledged agenda-driven data. But when the storytellers are traditional media, I’ll take data, even from suspect institutions, any day.
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This is a terrible article about bad research. The original research is ill-conceived and apparently driven by some sort of vague ecofeminist research question to find gender differences but it at least makes a half-assed attempt to factor by household type, urban-rural etc.
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The Guardian article mangles even that, ignores all nuances, juxtaposes with random pointers to “related” issues like climate impact of child-bearing. The result is a dumb article that elides everything actually salient while pushing a zero-sum gender-war framing.
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I couldn’t have asked for a more perfect example of the “zero-sum transform” phenomenon I did a thread about yesterday. The Guardian article is literally written to suggest that climate action is primarily a gender relations issue and that other details are rounding errors.
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Take a random issue, and consider a *random* take on it. As in, derived by situating it in a context induced by a random intention. Like: issue = “is icecream good?” Contexts: taste, biology, health, insecurity, science, climate… Is the take likely to be zero or nonzero-sum?
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I’m trying to make up good filter criteria for what makes for good climate reporting. Unfortunately there’s way more examples of bad than good, so I need to collect a good reference set of “good” first. Articles that exhibit real insight, rhetorical sophistication, and good faith
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