Faculty and Staff

In the wake of both the end of court-ordered school desegregation and the growing popularity of accountability as a mechanism to maximize student achievement, the authors explore the association between racial segregation and the percentage of students passing high-stakes tests in Florida's schools. Results suggest that segregation matters in predicting school-level performance on the Florida Comprehensive Assessment Test after control for other known and purported predictors of standardized test performance. Also, these results suggest that neither recent efforts by the state of Florida to equalize the funding of education nor current efforts involving high-stakes testing will close the Black-White achievement gap without consideration of the racial distribution of students across schools.

The spread of academic testing for accountability purposes in multiple countries has obscured at least two historical purposes of academic testing: community ritual and management of the social structure. Testing for accountability is very different from the purpose of academic challenges one can identify in community “examinations” in 19th century North America, or exams’ controlling access to the civil service in Imperial China. Rather than testing for ritual or access to mobility, the modern uses of testing are much closer to the state-building project of a tax census, such as the Domesday Book of medieval Britain after the Norman Invasion, the social engineering projects described in James Scott's Seeing like a State (1998), or the “mapping the world” project that David Nye described in America as Second Creation (2004). This paper will explore both the instrumental and cultural differences among testing as ritual, testing as mobility control, and testing as state-building.

Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.