Shortening Agency and Judicial Vacancies Through Filibuster Reform? An Examination of Confirmation Rates and Delays from 1981 to 2014

This Article explores the failure of nominations and the delay in confirmation of successful nominations across recent administrations, with a focus on the November 2013 change to the Senate voting rules. Using a new database of all nonroutine civilian nominations from January 1981 to December 2014, there are several key findings. First, approximately one-quarter of submitted nominations between 1981 and 2014 were not confirmed, with a higher failure rate for the last two Presidents. Nominations to courts of appeals and independent regulatory commissions had much higher failure rates than other entities. Second, for confirmed nominations, the time to confirmation has been increasing. President Obama’s nominees faced confirmation delays that were more than twice as long as President Reagan’s choices. Failure rates of nominations did not always go hand-in-hand with confirmation delays for successful nominations. Although more nominations failed in divided government, confirmation delays were roughly equal when different parties controlled the Senate and the White House. Third, comparing the year after the change to the filibuster rules to the preceding year, confirmation times for the courts decreased but increased for all types of agencies. For many agencies and agency positions, however, significantly fewer nominations failed after the voting change. Even so, these improvements in 2014—to the confirmation rates for both agency and judicial nominees and to the confirmation pace for judicial picks—are relative: for the average nomination, the failure rate was higher and the confirmation process was slower than under preceding administrations. Fourth, nearly 30 percent of nominees hailed from the District of Columbia, Maryland, and Virginia, raising concerns that the confirmation process may be narrowing the pool of top officials. This Article suggests some possible explanations for the findings and further avenues of investigation, and also proposes some reforms

Non-Statistical Factors Present in Successful NBA Rookies

Becoming a successful NBA rookie is a desire of many. Athletes want to be them and coaches and GM’s want to know how to predict them. What non-statistical factors are present in successful NBA rookies? This research used secondary data to show non-statistical factors that were present in successful rookies and what kind of similarities they had. They included, conference, institution, coaching, and draft position, etc... It is important to know what a successful rookie is and if there is a correlation between draft position and rookie success. The point of this research is to show the journeys that the successful rookies took before becoming successful rookies to help better understand what it takes to become a successful rookie

Seismic response to evolving injection at the Rotokawa geothermal field, New Zealand

Catalogs of microseismicity are routinely compiled at geothermal reservoirs and provide valuable insights into reservoir structure and fluid movement. Hypocentral locations are typically used to infer the orientations of structures and constrain the extent of the permeable reservoir. However, frequency-magnitude distributions may contain additional, and underused, information about the distribution of pressure. Here, we present a four-year catalog of seismicity for the Rotokawa geothermal field in the central Taupō Volcanic Zone, New Zealand starting two years after the commissioning of the 140 MWe Nga Awa Purua power station. Using waveform-correlation-based signal detection we double the size of the previous earthquake catalog, refine the location and orientation of two reservoir faults and identify a new structure. We find the rate of seismicity to be insensitive to major changes in injection strategy during the study period, including the injectivity decline and shift of injection away from the dominant injector, RK24. We also map the spatial distribution of the earthquake frequency-magnitude distribution, or b-value, and show that it increases from ∼1.0 to ∼1.5 with increasing depth below the reservoir. As has been proposed at other reservoirs, we infer that these spatial variations reflect the distribution of pressure in the reservoir, where areas of high b-value correspond to areas of high pore-fluid pressure and a broad distribution of activated fractures. This analysis is not routinely conducted by geothermal operators but shows promise for using earthquake b-value as an additional tool for reservoir monitoring and management