Death and the Penguin: modularity,alienation and organising

ABSTRACT

The originality of this paper lies in the ways in which it explores how the depiction of organised crime within Andrey Kurkov’s novel Death and the Penguin can inform our understanding of organisational modularity. This non-orthodox approach might open up new avenues of thought in the study of organisational modularity while further illustrating how novelistic worlds can inform accounts of organisational realities. Two main research questions underlie the paper. How can Andrey Kurkov’s novel further our understanding of the complexity of organisational worlds and realities by focusing our attention on different landscapes of organising? How does Kurkov’s novel help us grasp the concept of modularity by drawing attention to new forms of modular organisation? Drawing from our reading of Kurkov’s novel, we primarily explore organisational modularity through Kurkov’s depiction of organised crime and consider the themes of alienation and isolation in the context of modular organising.     

Child Poverty Measurement in the UK: Assessing Support for the Downgrading of Income-Based Poverty Measures

Social Indicators Research - In 2016 the UK’s Conservative Government radically changed the official approach to child poverty measurement, scrapping targets for income poverty and material...     

THE IMPACT OF THE INTRODUCTION OF THE U.K. MINIMUM WAGE ON THE EMPLOYMENT PROBABILITIES OF LOW‐WAGE WORKERS

This paper uses longitudinal data from three contrasting data sets (matched Labor Force Surveys, the British Household Panel Survey, and matched New Earnings Surveys) to estimate the impact of the introduction of the U.K. minimum wage (in April 1999) on the probability of subsequent employment among those whose wages would have needed to be raised to comply with the minimum. A difference‐in‐differences estimator is used, based on position in the wage distribution. No significant adverse employment effects are found for any of the four demographic groups considered (adult and youth, men and women) or in any of the three data sets used. (JEL: J38, J23)     

Learning about restoration of urban ecosystems: a case study integrating public participation,stormwater management,and ecological research

Restoration of ecosystem functions in urban environments is made challenging by 1) a public that often lacks understanding of ecological principles, 2) inadequate evidence of the effectiveness of restoration practices, and 3) difficulty integrating social and biophysical factors in studies of urban ecosystems. This paper describes a case study in which potential solutions to these challenges were explored. We facilitated collaborative learning through public participation in the design and implementation of an urban riparian buffer along a headwater stream in a neighborhood park, a process that was informed by ecological research. Learning outcomes were evaluated using surveys and qualitative assessment of discussion. Results indicated that participants’ knowledge about water quality problems associated with urbanization, stormwater, and nonpoint-source pollution increased, familiarity with stormwater management practices increased, and perceptions about the importance of stream ecosystem functions changed. In-stream monitoring of sediment delivery, as well as direct measurements of buffer infiltration capacity, provided early evidence of buffer effectiveness in prevention of sediment inputs to the stream and absorption of runoff from surrounding surfaces. This study provides a useful model for integration of collaborative learning through participation, ecological restoration, and ecological research in an urban setting. Elements deemed essential to success of this model included an opportunity for dialog focused on a specific natural feature, sustained interaction between participants and researchers, opportunities for hands-on participation by urban residents, and flexibility in restoration practice installation.     

Still Partners After All These Years: Ulrich's and ISSN

Since 2000, an Ulrich's Periodicals Directory (Ulrich's) employee has been located in the Library of Congress's U.S. ISSN Center at the Library of Congress to assign ISSN and create records for both Ulrich's and the international ISSN Register/CONSER database. How this arrangement came about, how it has succeeded over the past ten years, and the broad potential for this partnership becoming a model in both organizations for future automated data sharing and data linking is the subject of this article.     

Expanding the Scope of Responsible Conduct of Research Instruction

We argue that responsible conduct research (RCR) instruction should be extended beyond students and trainees funded by the National Institutes of Health (NIH) or National Science Foundation (NSF) to include all students, trainees, faculty, and research staff involved in research. Extending the scope of RCR instruction can help institutions develop and maintain an environment that promotes ethical research conduct. Universities and scientific organizations have objected to expanding the scope of RCR instruction on the grounds that it would be a major undertaking that would require the expenditure of additional institutional resources. We argue, however, that expanding the scope of RCR instruction can be done efficiently without placing undue burdens on institutions.     

Using expected values to simplify decision making under uncertainty

A simulation study examines the impact of a simplification strategy that replaces distributional attribute evaluations with their expected values and uses those expectations in an additive value model. Several alternate simplified forms and approximation approaches are investigated, with results showing that in general the simplified models are able to provide acceptable performance that is fairly robust to a variety of internal and external environmental changes, including changes to the distributional forms of the attribute evaluations, errors in the assessment of the expected values, and problem size. Certain of the simplified models are shown to be highly sensitive to the form of the underlying preference functions, and in particular to extreme non-linearity in these preferences.     

Testing Multiple Forecasters

We consider a cross‐calibration test of predictions by multiple potential experts in a stochastic environment. This test checks whether each expert is calibrated conditional on the predictions made by other experts. We show that this test is good in the sense that a true expert—one informed of the true distribution of the process—is guaranteed to pass the test no matter what the other potential experts do, and false experts will fail the test on all but a small (category I) set of true distributions. Furthermore, even when there is no true expert present, a test similar to cross‐calibration cannot be simultaneously manipulated by multiple false experts, but at the cost of failing some true experts.     

Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials

In behavioral, educational and medical practice, interventions are often personalized over time using strategies that are based on individual behaviors and characteristics and changes in symptoms, severity, or adherence that are a result of one's treatment. Such strategies that more closely mimic real practice, are known as dynamic treatment regimens (DTRs). A sequential multiple assignment randomized trial (SMART) is a multi-stage trial design that can be used to construct effective DTRs. This article reviews a simple to use ‘weighted and replicated’ estimation technique for comparing DTRs embedded in a SMART design using logistic regression for a binary, end-of-study outcome variable. Based on a Wald test that compares two embedded DTRs of interest from the ‘weighted and replicated’ regression model, a sample size calculation is presented with a corresponding user-friendly applet to aid in the process of designing a SMART. The analytic models and sample size calculations are presented for three of the more commonly used two-stage SMART designs. Simulations for the sample size calculation show the empirical power reaches expected levels. A data analysis example with corresponding code is presented in the appendix using data from a SMART developing an effective DTR in autism.