A geometric examination of Kemeny's rule

By using geometry, a fairly complete analysis of Kemeny's rule (KR) is obtained. It is shown that the Borda Count (BC) always ranks the KR winner above the KR loser, and, conversely, KR always ranks the BC winner above the BC loser. Such KR relationships fail to hold for other positional methods. The geometric reasons why KR enjoys remarkably consistent election rankings as candidates are added or dropped are explained. The power of this KR consistency is demonstrated by comparing KR and BC outcomes. But KR's consistency carries a heavy cost; it requires KR to partially dismiss the crucial “individual rationality of voters” assumption. Received: 5 February 1998/Accepted: 26 May 1999     

Consequences of Population Change for Retail/Wholesale Sector Employment in the Nonmetropolitan Great Plains: 1950–19961

Abstract A rural economic restructuring perspective and central place theory are used to assess the impact of population change on retail/wholesale sector employment for the 438 nonmetropolitan counties of the Great Plains region from 1950 to 1990. Findings indicate that county level population declined for every decade except the 1970 turnaround decade, and the greatest losses were in completely rural nonadjacent counties. The civilian labor force declined for all but the 1970 decade, when there was a substantial increase due to increased nonmetro manufacturing and the baby boom cohorts reaching labor force age. Retail/wholesale labor force increased in every decade except the 1980s. However, regression analysis found a positive and highly significant relationship between population change and retail/wholesale employment change. For this region, population decline is a major contributor to decline in the retail/wholesale employment sector at the county level. Preliminary data from the 1990–1996 period indicate a population and labor force rebound from the 1980s. However, as in the 1980s, gains are most likely concentrated in a small number of mainly urban nonadjacent counties.     

Ellenore Flood's Kuder Occupational Interest Survey and Career Search Schedule

The Kuder Occupational Interest Survey and Career Search Schedule are interpreted for a client (given the pseudonym Ellenore Flood) in the form of a letter addressed to her. Comments on technique, the author's reasoning, and suggestions for further interventions are interpolated throughout.     

News that takes your breath away: risk perceptions during an outbreak of vaping-related lung injuries

Journal of Risk and Uncertainty - We study the impact of new information on people’s perceptions of the risks of e-cigarettes. In September 2019 the U.S. experienced an outbreak of...     

Missing data estimators in the general linear model: an evaluation of simulated data as an experimental design

Previous simulations have reported second order missing data estimators to be superior to the more straightforward first order procedures such as mean value replacement. These simulations however were based on deterministic comparisonsbetween regression criteria even though simulated sampling is a random procedure. In this paper a simulation structured asan experimental design allows statistical testing of the various missing data estimators for the various regression criteria as well as different regression specifications. Our results indicate that although no missing data estimator is globally best many of the computationally simpler first order methods perform as well as the more expensive higher order estimators, contrary to some previous findings.