We extend classical ideal point estimation to allow voters to have different preferences when voting in different domains—for example, when voting on agricultural policy than when voting on defense policy. Our scaling procedure results in estimated ideal points on a common scale. As a result, we are able to directly compare a member’s revealed preferences across different domains of voting (different sets of motions) to assess if, for example, a member votes more conservatively on agriculture motions than on defense. In doing so, we are able to assess the extent to which voting behavior of an individual voter is consistent with a uni-dimensional spatial model—if a member has the same preferences in all domains. The key novelty is to estimate rather than assume the identity of “stayers”—voters whose revealed preference is constant across votes. Our approach offers methodology for investigating the relationship between the basic space and issue space in legislative voting (Poole 2007). There are several methodological advantages to our approach. First, our model allows for testing sharp hypotheses. Second, the methodology developed can be understood as a kind of partial-pooling model for item response theory scaling, resulting in less uncertainty of estimates. Related, our estimation method provides a principled and unified approach to the issue of “granularity” (i.e., the level of aggregation) in the analysis of roll-call data (Crespin and Rohde 2010; Roberts et al. 2016). We illustrate the model by estimating U.S. House of Representatives members’ revealed preferences in different policy domains, and identify several other potential applications of the model including: studying the relationship between committee and floor voting behavior; and investigating constituency influence and representation.

The results of Bayesian analysis using 43 new high-precision AMS radiocarbon dates on maize, faunal remains, and ceramic residues from 18 precontact Iroquoian village sites in Northern New York are presented. Once thought to span AD 1350–1500, the period of occupation suggested by the modeling is approximately AD 1450–1510. This late placement now makes clear that Iroquoians arrived in the region approximately 100 years later than previously thought. This result halves the time in which population growth and significant changes in settlement occurred. The new chronology allows us to better match these events within a broader Northeast temporal framework.

Although disaster-related posttraumatic stress symptoms (PTSS) typically decrease in intensity over time, some youth continue to report elevated levels of PTSS many years after the disaster. The current study examines two processes that may help to explain the link between disaster exposure and enduring PTSS: caregiver emotion socialization and youth recollection qualities. One hundred and twenty-two youth (ages 12 to 17) and their female caregivers who experienced an EF-4 tornado co-reminisced about the event, and adolescents provided independent recollections between 3 and 4 years after the tornado. Adolescent individual transcripts were coded for coherence and negative personal impact, qualities that have been found to contribute to meaning making. Parent–adolescent conversations were coded for caregiver egocentrism, a construct derived from the emotion socialization literature to reflect the extent to which the caregiver centered the conversation on her own emotions and experiences. Egocentrism predicted higher youth PTSS, and this association was mediated by the coherence of adolescents’ narratives. The association between coherence and PTSS was stronger for youth who focused more on the negative personal impacts of the tornado event during their recollections. Results suggest that enduring tornado-related PTSS may be influenced in part by the interplay of caregiver emotion socialization practices and youth recollection qualities.