The sustainable fashion conversation is based on bad statistics and misinformation – Vox
I pulled all of these statistics and other common “facts” from reputable sources. McKinsey. The United Nations. The Ellen MacArthur Foundation. The World Bank. International labor unions. Advocacy organizations. And these facts have been cited by publications like the Wall Street Journal and the New York Times. Not all of these highly respected experts could be wrong. Could they? It turns out they could. Because only one out of the dozen or so most commonly cited facts about the fashion industry’s huge footprint is based on any sort of science, data collection, or peer-reviewed research. The rest are based on gut feelings, broken links, marketing, and something someone said in 2003.
(tags: bad-data data facts factoids misinformation fashion fast-fashion climate-change)
the CO2 footprint of email is greatly exaggerated
If you care about the environmental impact of tech, worrying about email is not the place to spend your time and energy. Worry instead about the big tech companies accelerating the extraction of fossil fuels, when we need to keep them in the ground. [….] Worry instead about consulting companies you admire doing the same, and helping the same oil and gas companies, but keeping quiet about doing so. Worry about how blase we are about flying when it makes up a significant chunk of company emissions in many tech consultancies and enterprise sales teams.
(tags: climate-change email factoids misinformation carbon)
(tags: histograms aggregation quantiles percentiles measurement graphs data-structures summaries latency monitoring approximation papers)
A minimalist dashboard style using horizon charts:
Horizon charts reduce vertical space without losing resolution. Larger values are overplotted in successively darker colors, while negative values are offset to descend from the top. As you increase the number of colors, you reduce the required vertical space […] . By combining position and color, horizon charts improve perception: position is highly effective at discriminating small changes, while color differentiates large changes. To further increase data density, Cubism favors per-pixel metrics where each pixel encodes a distinct point in time. Cubism also includes thoughtful default colors by Cynthia Brewer.