Helpers “Here on the Front Lines”: Welfare‐to‐Work Managers' Moral Identity Work

Using data drawn from telephone interviews with Ohio Works First program managers (N = 69), we examine managers' moral identity work. This work included using militarized rhetoric to evoke moral identities as honorable workers. It also involved signifying helper/helpful moral identities by defining what it means to be helpful, legitimating their helper identity through connections to caseworkers, and affirming their identity through telling success stories. Additionally, managers implicitly othered clients they viewed as needy and politicians they considered to be out‐of‐touch. Our research contributes to the literature on welfare‐to‐work, but also more broadly to our understanding of moral identity work and implicit othering.     

Preschoolers' Bistrategic Resource Control,Reconciliation, and Peer Regard

Bistrategic resource control entails using both coercive and prosocial strategies in competition for resources. The present study sought to clarify whether bistrategic involves more than simply using both strategies some of the time. Examining 88 preschoolers' coercion and prosociality over an entire school year, results showed that coercive resource control was used most frequently at the start of the school year, presumably to access resources and establish social dominance. Rates of prosocial resource control increased over the school year, and socially dominant preschoolers showed higher rates compared with peers, presumably to maintain resource control while keeping peers as allies. Socially dominant preschoolers also used reconciliation more often than peers, resulting in higher rates of affiliation between former competitors and more positive peer regard from fall to spring. Findings are discussed in terms of resource control theory and the importance of situating social behaviors within the behavioral and relationship context in which they are embedded.     

Improving confidence in tree species selection for challenging urban sites: a role for leaf turgor loss

High species diversity is argued to be the most important requisite for a resilient urban forest. In spite of this, there are many cities in the northern hemisphere that have very limited species diversity within their tree population. Consequently, there is an immense risk to urban canopy cover, if these over-used species succumb to serious pests or pathogens. Recognition of this should motivate the use of less commonly used species. Analysis of plant traits, such as the leaf water potential at turgor loss (Ψ_P0), can provide useful insights into a species’ capacity to grow in warm and dry urban environments. Therefore, the aim of this study was to evaluate Ψ_P0 of 45 tree species, the majority of which are rare in urban environments. To help evaluate the potential for using Ψ_P0 data to support future decision-making, a survey of professionals engaged with establishing trees in urban environments was also used to assess the relationship between the measured Ψ_P0 and the perceived drought tolerance of selected species. This study demonstrates that Ψ_P0 gives strong evidence for a species’ capacity to tolerate dry growing conditions and is a trait that varies substantially across species. Furthermore, Ψ_P0 was shown to closely relate to the experience of professionals involved in establishing trees in urban environments, thus providing evidence of its practical significance. Use of plant traits, such as Ψ_P0, should, therefore, give those specifying trees confidence to recommend non-traditional species for challenging urban environments.     

Mixtures of modified t-factor analyzers for model-based clustering,classification, and discriminant analysis

A novel family of mixture models is introduced based on modified t-factor analyzers. Modified factor analyzers were recently introduced within the Gaussian context and our work presents a more flexible and robust alternative. We introduce a family of mixtures of modified t-factor analyzers that uses this generalized version of the factor analysis covariance structure. We apply this family within three paradigms: model-based clustering; model-based classification; and model-based discriminant analysis. In addition, we apply the recently published Gaussian analogue to this family under the model-based classification and discriminant analysis paradigms for the first time. Parameter estimation is carried out within the alternating expectation-conditional maximization framework and the Bayesian information criterion is used for model selection. Two real data sets are used to compare our approach to other popular model-based approaches; in these comparisons, the chosen mixtures of modified t-factor analyzers model performs favourably. We conclude with a summary and suggestions for future work.     

You Wouldn't Like Me When I'm Angry: List Experiment Misreporting*

Objective. List experiment respondents may misreport the number of list items that they associate with in order to associate themselves with a socially desirable test item or to disassociate themselves from a socially undesirable test item. Tests for such misreporting were conducted. Methods. List experiments from the 1991 National Race and Politics Survey, the 2006 Cooperative Congressional Election Study, and the 2008 Cooperative Campaign Analysis Project were analyzed or reviewed. Results. Evidence suggested that some respondents deflated their report more than necessary to avoid association with a socially undesirable test item. Conclusions. List experiments may provide inaccurate estimates of the percentage of the population to which the test item applies, but the direction of bias is predictable.     

Doing Good,Public Good,and Public Value

In this article, using multiple illustrative case examples, we demonstrate that philanthropic institutions are in the business of creating public value. In framing the work of philanthropy more broadly to include the process of public value creation, philanthropic institutions and leaders are challenged to be more strategic not only in their mission‐fulfillment grant‐making with nonprofit organizations but also in the way they stimulate and encourage collaboration, create the “third space” necessary to incubate ideas to transform society, and leverage resources to increase the return on their investments toward system‐wide change. The implications for philanthropic actors and institutions suggest that the strategic contributions they make toward creation of public value are those that go beyond transactional performance measures, such as number of dollars spent or clients receiving services, to include ways that their investments are amplified by meaningful partnerships with nonprofit and other organizations, changed behaviors of institutions and individuals, and transformative public policies.     

Dirichlet models for square contingency tables

We consider the square contingency tables which arise when the same method of classification is applied twice. The hypothesis of marginal homogeneity is then relevant! and can be tested by various methods Models are discussed which contain marginal homogeneity as a special case. They include a class based on univariate and bivariate Dirichlet distributions. The question of ordered categories is briefly discussed. Applications are made to data on unaided distance vision.     

A new prototype system for optimized job shop scheduling

Optimal scheduling of shopfloor activities in an environment of discrete part manufacturing is discussed. The scheduling problem is a well known NP complete one. The main part, the sequencing problem, has been tackled using two techniques: virtual resources identification and taboo search heuristics. The first approach allowed the authors to reduce the complexity of the sequencing from a job shop to a general flow shop problem. On the other hand, the search for an optimal solution, with respect to a fixed strategy, has been achieved via the taboo search. A synthesis of the results of a large number of tests is presented as well as the results of an application to a real case. The latter is shown in comparison with the output of the system being presently used in the examined factory.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.