Scale, quality and efficiency in road maintenance: Evidence for English local authorities

This paper outlines the first econometric stochastic frontier efficiency analysis of road maintenance costs for local authorities in England in the academic literature. It is motivated by current public sector austerity requiring local authorities to provide efficient highway functions both in terms of learning from best practice (economic efficiency) and potential reorganisation to exploit economies of scale (scale efficiency). The analysis utilises a road condition measure and an end user (public) satisfaction indicator as well as road length and traffic factors. The availability of public satisfaction data is particularly important as incorporation of such a measure into benchmarking is currently in its infancy in economic regulation but is increasing in prominence, such as in regulation of health care. Evidence is found for an optimal road length which has implications for the current trend to merge the delivery of highways services across local authorities. Bigger is not necessarily better. A positive relationship is found between public satisfaction and cost which is strongest for very low or high public satisfaction. Finally, the median cost efficiency is 83% which implies many authorities have the opportunity to save substantial sums by adopting best practice without reducing service quality

Grief Content Inclusion in CACREP-Accredited Counselor Education Programs

This study investigated how counselor educators (n = 61) integrated grief content in accredited counselor education programs, characteristics of the course in which grief is taught, and professional background of faculty members. Most participants endorsed general content items (e.g., reactions to loss), grief theories (e.g., stages/phases of grief), and practice considerations (e.g., self-care). Additionally, results indicated grief-focused courses were mostly elective (n = 23; 85.19%), facilitated face-to-face (n = 18; 66.67%) and taught by counselor educators influenced by significant personal loss (n = 18, 78.26%). Results demonstrated a lack of professional affiliation with grief-related organizations, professional development through certifications, or continuing education. Discussion of results, implications for the counseling profession, and areas for future research and practice are explored

SensePath: understanding the sensemaking process through analytic provenance

Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user’s sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process

Analytic provenance for sensemaking: a research agenda

Sensemaking is a process of find meaning from information, and often involves activities such as information foraging and hypothesis generation. It can be valuable to maintain a history of the data and reasoning involved, commonly known as provenance information. Provenance information can be a resource for “reflection-in-action” during analysis, supporting collaboration between analysts, and help trace data quality and uncertainty through analysis process. Currently, there is limited work of utilizing analytic provenance, which captures the interactive data exploration and human reasoning process, to support sensemaking. In this article, we present and extend the research challenges discussed in a IEEE VIS 2014 workshop in order to provide an agenda for sensemaking analytic provenance

The case for the use of multiple imputation missing data methods in stochastic frontier analysis with illustration using English local highway data

Multiple Imputation (MI) methods have been widely applied in economic applications as a robust statistical way to incorporate data where some observations have missing values for some variables. However in Stochastic Frontier Analysis (SFA), application of these techniques has been sparse and the case for such models has not received attention in the appropriate academic literature. This paper fills this gap and explores the robust properties of MI within the stochastic frontier context. From a methodological perspective, we depart from the standard MI literature by demonstrating, conceptually and through simulation, that it is not appropriate to use imputations of the dependent variable within the SFA modelling, although they can be useful to predict the values of missing explanatory variables. Fundamentally, this is because efficiency analysis involves decomposing a residual into noise and inefficiency and as a result any imputation of a dependent variable would be imputing efficiency based on some concept of average inefficiency in the sample. A further contribution that we discuss and illustrate for the first time in the SFA literature, is that using auxiliary variables (outside of those contained in the SFA model) can enhance the imputations of missing values. Our empirical example neatly articulates that often the source of missing data is only a sub-set of components comprising a part of a composite (or complex) measure and that the other parts that are observed are very useful in predicting the value

SensePath: Understanding the Sensemaking Process Through Analytic Provenance

Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process

CASE STUDY OF AN ACCIDENTAL ANKLE TWIST: A KINEMATIC ANALYSIS USING FUNCTIONAL DATA ANALYSIS

This study examined an accidental ankle twist occurring during a single-participant study of the effects of traction on ankle biomechanics. One male participant performed a series of randomly distributed side-cuts and turns. In the 11th trial, the participant twisted his ankle during a side-cut. As no injury occurred, another 24 side-cut trials were recorded. Functional Data Analysis (FDA) demonstrated that the ankle twist trial was characterised by a sudden increase in inversion and internal rotation along with rapid transition from plantarflexion to dorsiflexion. Velocities showed a two-step increase in internal rotation and inversion, exceeding a 300 °/s safety threshold. The shift to dorsiflexion is indicative of an unloading mechanism that likely prevented the injury. FDA revealed variations between the ankle twist and the control that could inform stud design to prevent injuries

Analytic provenance for sensemaking: A research agenda

Sensemaking is a process of finding meaning from information that often involves activities such as information foraging and hypothesis generation. It can be valuable to maintain a history of the data and reasoning involved. This history, commonly known as provenance information, can be a resource for 'reflection-in-action'' during analysis, supporting collaboration between analysts, and can help trace data quality and uncertainty through the analysis process. Currently, there is limited work on utilizing analytic provenance, which captures the interactive data exploration and human reasoning process, to support sensemaking. This article presents and extends the research challenges discussed in a IEEE VIS 2014 workshop on this topic to provide an agenda for sensemaking analytic provenance

Pulmonary histoplasmosis presenting as chronic productive cough, fever, and massive unilateral consolidation in a 15-year-old immune-competent boy: a case report

Severe histoplasmosis is known to be among the AIDS-defining opportunistic infections affecting patients with very low CD4 cell counts in histoplasmosis-endemic areas. Histoplasma capsulatum var. duboisii is common in West and Central Africa, where it occurs in both HIV/AIDS and non-HIV patients. Few cases of life-threatening histoplasmosis in immune-competent individuals have been reported worldwide. We describe a case of pulmonary histoplasmosis diagnosed on the basis of autopsy and histological investigations. A 15-year old East African immune-competent boy with a history of smear-positive tuberculosis and a two-year history of rock cutting presented to our hospital with chronic productive cough, fever, and massive unilateral consolidation. At the time of presentation to our hospital, this patient was empirically treated for recurrent tuberculosis without success, and he died on the seventh day after admission. The autopsy revealed a huge granulomatous lesion with caseation, but no acid-fast bacilli were detected on several Ziehl-Neelsen stains. However, periodic acid-Schiff staining was positive, and the histological examination revealed features suggestive of Histoplasma yeast cells. Severe pulmonary histoplasmosis should be considered in evaluating immune-competent patients with risk factors for the disease who present with pulmonary symptoms mimicking tuberculosis