Attempts To Put Statistics In Context, Put Into Context

Argues that 'putting a statistic in context' is easily weaponised: any effect size or correlation can be made to sound trivial or enormous by choosing the comparison (IQ-vs-grades r=0.54 can be framed as 'explains <30% of variance' or 'bigger than party-vs-Trump-support'). Offers a genuinely useful antidote -- a long reference list of real effect sizes (DARE 0.02, single-sex schools 0.08, SSRIs 0.4, Adderall 1.3, men-taller-than-women 1.7, individual tutoring 2.0) and correlations (brain size vs IQ 0.19, IQ vs educational attainment 0.44, IQ vs grades 0.54, SAT-verbal vs SAT-math 0.72, same student's SAT twice 0.87) -- while noting a statistician's caveat that domain-specific units often beat standardized ones.

Quality 66 · Strong. Strong/Solid edge. A sound methodological caution plus a handy, oft-referenced effect-size/correlation table; the lasting value is the reference list. Short and partly a compilation, so mid-Solid-to-Strong.

Claude’s paradigm shift 42 · Moderate. Moderate. The context-is-manipulable point is mildly fresh; the table is a compilation of others' numbers.

Real-world impact 2 · Minor. Minor. A useful statistical-literacy reference within the rationalist/stats discourse; no material reach. Within-niche.