Her examples were well chosen (Bangladesh, California) but were somewhat few and far between: she was somewhat relentless is keeping to a high level of abstraction.
Her background was in physics and gravity, which to Tara made a lot of sense, explained her attitudes, her sense of certainty. Nancy said she only dared venture into more mushy terrain once assured of tenure. Many tenured are not nearly that brave, taking few if any risks.
If you educate young mothers about nutrition they will make better decisions when procuring foods, randomized studies show. What if mothers aren't permitted to procure? If you halve class size, disadvantaged children will especially benefit from the increased attention, studies show (and people believe). Yet doubling the number of teachers may flood the system with many unqualified and physical space may be in short supply, resulting in many vital courses getting crowded out by mediocre "more of the same".
The Speech & Debate community was there in some force (thanks to Mentor Graphics Foundation), Rose spotting Tara (old team mates reunited). I sat with other board, Steve Holden, hangers-on (smile). Terry was relaxed at the podium and effusive in his praise for Nancy, even though she's "terrified" of global warming (as she made clear during the Q&A (Terry sometimes poses as a skeptic (on many things controversial where the neg position seems poorly defended))).
Actually, thinking back, that was pretty bold what Terry did, taking on Icahn by the horns and defending Mentor's current management as community minded. That's what's so threatening to cowardly investors who hide behind rapacious money-making machinery that wreaks havoc, externalizes all risk (impossible on a spherical planet, where what goes around comes around -- quite literally).
Nancy's thesis: whereas the empiricists are right to thump the table in favor of randomized controlled studies, they're often just as confused about what these studies might legitimately establish or assert as the non-empirically minded. Her talk reminded me of Tom Siegfried's, as his message was similar: people don't get it about statistics, even when you think they would given their job descriptions as scientist types.
Causes need contributing factors to work their magic, catalysts. They're insufficient by themselves, nor are they necessary in the sense that if p then q, q, therefore p doesn't follow. You might get q for other reasons. Lung cancer need not be caused by cigs, which doesn't mean cigs don't cause lung cancer.