The Social Context of Police Lying

This is an analysis of the social context of normal police lies. We define lies as speech acts which the speaker knows are misleading or false, are intended to deceive, and where evidence to the contrary is known to the observer. Lies are relative to a moral context, and what an audience will accept. Lies include excuses, which deny full responsibility for an act, but acknowledge its immorality, and justifications, which accept responsibility but deny blame-worthiness. Police learn to lie and to carefully distinguish normal (or acceptable) lies from unacceptable lies, suggesting that lies are a part of a negotiated occupational order. We show how and why some types of lies are rewarded by police using ethnographic data from an 18 month field study of a large urban force. Lies can be of little issue, or become troublesome. We report and analyze two kinds of troublesome lies: case lies, recognized stories an officer utilizes in a courtroom or on paper to facilitate the conviction of a suspect, and cover stories, lies an officer tells in court, to supervisors, and on the job with the aim of providing a verbal shield or mitigation in the event of discipline. Both excuses and justifications are woven together in these vignettes. An example of a refusal to lie is used to illustrate some of the limits on lying as well organizational factors in lying. Some implications for official lying are also noted.     

Bayesian analysis of outlier problems using divergence measures

A Bayesian approach is presented for detecting influential observations using general divergence measures on the posterior distributions. A sampling-based approach using a Gibbs or Metropolis-within-Gibbs method is used to compute the posterior divergence measures. Four specific measures are proposed, which convey the effects of a single observation or covariate on the posterior. The technique is applied to a generalized linear model with binary response data, an overdispersed model and a nonlinear model. An asymptotic approximation using Laplace method to obtain the posterior divergence is also briefly discussed.     

Who Gets What From Government? Distributional Consequences of Child‐Care Assistance Policies

Given the fragmented structure of child‐care assistance in the United States, it has been difficult to obtain accurate estimates of which families are assisted, through which mechanisms, and at what level. Making use of survey data from New York City, we analyze the distribution of several forms of public child‐care assistance. Results suggest that about 40% of all families with young children receive some form of child‐care assistance. Considering all forms of assistance, the distribution of child‐care help is targeted in both expected and some unexpected ways. Implications of these results are discussed in the context of U.S. child‐care policies governing access and benefit levels.     

The role of family help in the housing decisions of young people

Recent debates about flows of help within the family have indicated considerable diversity according to the type of help (money, services), and ages and gender of those involved, and have shown that values are only a partial guide to the scale of such flows. This paper focuses on a particular occasion for help, young people's housing, and a particular region, South-East England, where one would expect family financial help to be high given the capacity to help of older generations (due to higher average incomes and wealth) and the affordability problems faced by young people. It is shown that contrary to hypothesis only 12% of a sample of young people had received financial help for housing purposes since they had left home, less than found in previous studies with different samples. The amounts involved were less than young people believed their parents could afford. The role of inheritance was also found to be minor. The results from the different studies are explained as due to changes in the housing market, changing values regarding financial help and differences among the samples. Intensive re-interviews with three households from very different backgrounds are used to show the different ways in which family help operates.     

Exposure Reconstruction for the TCDD-Exposed NIOSH Cohort Using a Concentration- and Age-Dependent Model of Elimination

Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.     

A Numerical Solution to the Nonhomogeneous Two-Stage MVK Model of Cancer

In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.