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 * Ryskin, Qi, Duff, & Brown-Shmidt (2016). [[https://www.ncbi.nlm.nih.gov/pubmed/27762578|Verb Biases Are Shaped Through Lifelong Learning]]. People can learn new verb biases for argument interpretation -- e.g. in "Bop the bunny with the flower", "bop" biases ppl to interpret "with the flower" as an instrument rather than attribute of the bunny. Here they show that ppl can adapt to these preferences with repeated exposure to initially unbiased verbs.

Lab Meeting, Fall 2016, Week 10

Awe- and Aw-inspiring readings (or just stuff you think deserves a mention)

What we did over last week

Florian

Xin

Andrew

Jenn

Dan

Amanda

  1. Talked to the KurTan lab about my uncertainty with approaching uncertainty as a topic of study.

  2. Finished reading judith's paper, thought about it a bunch, failed to send her notes. will do so this week.
  3. Met with Si On Yoon about a collaboration / plan to look at an aspect of uncertainty on the kinds of expectations listeners might have for how a speaker is likely to label a thing.
  4. Emailed with Geertje about an eigenlijk follow up project / maybe setting up shop at the MPI for a bit next summer, if I'm going to be in Europe for a bit.
  5. Met with Chigusa and Wes about Wes' study. Thought of an interesting follow up.
  6. Asked Greg for a reference letter for a scholarship I'm applying for via the APA.
  7. Wrote a first draft abstract for the CSLI workshop at Stanford.
  8. Worked on my APA scholarship application, tried to work through some of the study ideas.
  9. Thought about Huang and Snedeker (2013) for the APA and as a first setup for the new eyetracker in the Kinder Lab.

Zach

Linda

Wednesday

Shaorong

  1. Revising the ERP proposal
  2. Did some straightforward math for contextual diversity and realized that our hypothesis only hold under very specific assumptions. Ran into Frank and talked to him about the problem, he suggested using long-tail prior like zipf distribution. Will try that.
  3. Analyzed data for NRT course. Null effect. And also the intercept is in the opposite direction as predicted by the model.

LabmeetingAU16w10 (last edited 2016-11-03 16:12:33 by WednesdayBushong)

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