Hospital-sponsored networks. The rush to consolidate and the future of medical practice

As the medical delivery system undergoes fundamental change, there is a growing pressure on hospitals to form networks with physicians. The prime motivation for these entities is to preserve market share and fill beds. There is likewise intense pressure on physicians to join them, even if these networks do not serve their best interests, or the goal of fostering physician-centered practice. A transformation is under way, however, that may well place doctors again in the central role of guiding the new modes of medical practice in the United States.     

Hierarchy or co-operation: labour-management relations in church institutions

Aspects of industrial relations and internal co-ordination have been a major topic of empirical research in the German business enterprise sector. In contrast, there are practically no empirical investigations into labour-management relations in third sector institutions. The largest share of this sector in Germany is represented by the two Christian churches with presently about 900,000 employees. According to the notion of church officials, labour-management relations in these institutions are characterised by a specific normative concept which emphasises a trustful co-operation of all employees in the mission of the church. The major concern of our research project focused on the question whether the specific conditions of employment within church institutions favour more hierarchical or more co-operative forms of co-ordination and how employees and employee representatives perceive the ideal of the community of service (Dienstgemeinschaftsgedanke). The results of our research lead to the conclusion that church labour-management relations are characterised by a remarkable contrast between the participative or co-operative notion of the ideal of the community of service and present forms of hierarchical co-ordination inside church institutions.This article gives a selected overview of Beyer and Nutzinger (1991). The research was supported by the Hans-Böckler-Stiftung (Düsseldorf) and the University of Kassel.     

Compliance Versus Risk in Assessing Occupational Exposures

Assessments of occupational exposures to chemicals are generally based upon the practice of compliance testing in which the probability of compliance is related to the exceedance [γ, the likelihood that any measurement would exceed an occupational exposure limit (OEL)] and the number of measurements obtained. On the other hand, workers’ chronic health risks generally depend upon cumulative lifetime exposures which are not directly related to the probability of compliance. In this paper we define the probability of “overexposure” (θ) as the likelihood that individual risk (a function of cumulative exposure) exceeds the risk inherent in the OEL (a function of the OEL and duration of exposure). We regard θ as a relevant measure of individual risk for chemicals, such as carcinogens, which produce chronic effects after long-term exposures but not necessarily for acutely-toxic substances which can produce effects relatively quickly. We apply a random-effects model to data from 179 groups of workers, exposed to a variety of chemical agents, and obtain parameter estimates for the group mean exposure and the within- and between-worker components of variance. These estimates are then combined with OELs to generate estimates of γ and θ. We show that compliance testing can significantly underestimate the health risk when sample sizes are small. That is, there can be large probabilities of compliance with typical sample sizes, despite the fact that large proportions of the working population have individual risks greater than the risk inherent in the OEL. We demonstrate further that, because the relationship between θ and γ depends upon the within- and between-worker components of variance, it cannot be assumed a priori that exceedance is a conservative surrogate for overexposure. Thus, we conclude that assessment practices which focus upon either compliance or exceedance are problematic and recommend that employers evaluate exposures relative to the probabilities of overexposure.     

Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Dynamic Pricing to Minimize Maximum Regret

We consider a dynamic pricing problem that involves selling a given inventory of a single product over a short, two‐period selling season. There is insufficient time to replenish inventory during this season, hence sales are made entirely from inventory. The demand for the product is a stochastic, nonincreasing function of price. We assume interval uncertainty for demand, that is, knowledge of upper and lower bounds but not a probability distribution, with no correlation between the two periods. We minimize the maximum total regret over the two periods that results from the pricing decisions. We consider a dynamic model where the decision maker chooses the price for each period contingent on the remaining inventory at the beginning of the period, and a static model where the decision maker chooses the prices for both periods at the beginning of the first period. Both models can be solved by a polynomial time algorithm that solves systems of linear inequalities. Our computational study demonstrates that the prices generated by both our models are insensitive to errors in estimating the demand intervals. Our dynamic model outperforms our static model and two classical approaches that do not use demand probability distributions, when evaluated by maximum regret, average relative regret, variability, and risk measures. Further, our dynamic model generates a total expected revenue which closely approximates that of a maximum expected revenue approach which requires demand probability distributions.     

Charisma as signal: An evolutionary perspective on charismatic leadership

We present an evolutionary perspective on charismatic leadership, arguing that charisma has evolved as a credible signal of a person's ability to solve a coordination challenge requiring urgent collective action from group members. We suggest that a better understanding of charisma's evolutionary and biological origins and functions can provide a broader perspective in which to situate current debates surrounding the utility and validity of charismatic leadership as a construct in the social sciences. We outline several key challenges which have shaped our followership psychology, and argue that the benefits of successful coordination in ancestral environments has led to the evolution of context-dependent psychological mechanisms which are especially attuned to cues and signals of outstanding personal leadership qualities. We elaborate on several implications of this signaling hypothesis of charismatic leadership, including opportunities for deception (dishonest signaling) and for large-scale coordination.     

Explaining the Flight of Cupid’s Arrow: A Spatial Random Utility Model of Partner Choice

Spatial homogamy may be defined as follows: anyone may be attracted to anyone else, but near candidates are more attractive than distant candidates. In this article, we propose a model of partner choice, where homogamy is defined in terms of spatial, demographic, socioeconomic and cultural similarity. A spatial choice model using random utility theory is formulated, taking into account a relaxation of the independence from the irrelevant alternatives property, as spatial alternatives are not independent of one another. We model partner choice given the characteristics of the chosen partner and a choice set of alternatives, using unique micro data on all new cohabiters in the Netherlands, linked to other relevant data sets. The model takes the spatial locations of potential candidates within a choice set into account, including an indicator for the spatial similarity between alternatives. We find that spatial homogamy is a vital component of partner matching, aside from and adding to the spatial effects in demographic, socioeconomic and cultural homogamy. Given a choice set of partners, the highest likelihood of a match occurs with a person who is born and lives near by, who is close in age, is in the same life stage and has the same marital status, who has the same educational and income level and the same labour market status, who speaks the same dialect and lives in a culturally similar residential area. The distance effect is most pronounced for those individuals with lower levels of education and those living in rural areas.     

Attenuating Initial Beliefs: Increasing the Acceptance of Anthropogenic Climate Change Information by Reflecting on Values

Anthropogenic climate change information tends to be interpreted against the backdrop of initial environmental beliefs, which can lead to some people being resistant toward the information. In this article (N = 88), we examined whether self‐affirmation via reflection on personally important values could attenuate the impact of initial beliefs on the acceptance of anthropogenic climate change evidence. Our findings showed that initial beliefs about the human impact on ecological stability influenced the acceptance of information only among nonaffirmed participants. Self‐affirmed participants who were initially resistant toward the information showed stronger beliefs in the existence of climate change risks and greater acknowledgment that individual efficacy has a role to play in reducing climate change risks than did their nonaffirmed counterparts.     

In the flesh: a poetic inquiry into how fat female employees manage weight-related stigma

ABSTRACT

This paper engages with the question of how fat female employees manage weight-related stigma at work. We use poetic inquiry to show the reader how it feels for our participants to be stigmatized based on their size. We interviewed 22 women who self-identify as full-figured, fat, overweight, or obese. The results consist of six poems, five of which were written by us, the researchers. These ‘tri-voiced poems’ (Leavy 2010b) illustrate the spectrum of affective responses and stigma management strategies that our participants talked about, ranging from feeling anxious, super-smart, impeccable, and funny to rebellious and confident. The sixth poem was written by one of our participants and voices her first-person experiences and perspective. Our aim is to do justice in our writing to the emotions that circulated in the interviews and to make a political statement with regards to the stigmatizing practices in organizations related to size and health.