Time, Self, and the Curiously Abstract Concept of Agency*

The term "agency" is quite slippery and is used differently depending on the epistemological roots and goals of scholars who employ it. Distressingly, the sociological literature on the concept rarely addresses relevant social psychological research. We take a social behaviorist approach to agency by suggesting that individual temporal orientations are underutilized in conceptualizing this core sociological concept. Different temporal foci—the actor's engaged response to situational circumstances—implicate different forms of agency. This article offers a theoretical model involving four analytical types of agency ("existential,""identity,""pragmatic," and "life course") that are often conflated across treatments of the topic. Each mode of agency overlaps with established social psychological literatures, most notably about the self, enabling scholars to anchor overly abstract treatments of agency within established research literatures.     

Gender and the 'New Paradigm' of Health

This article provides a critical review of literature on the relationship between gender and the 'new paradigm' of health. An overview of the feminist critique of health is given, from the Women's Health Movement of the late 1960s and early feminist debates about medicalisation, to more recent discussions about structural inequalities between men and women, eating disorders, and AIDS. I then go on to explore the feminist response to the so-called 'new paradigm' of health (an approach that emphasises health promotion, individual responsibility for health, and body-monitoring). Arguments that health promotion initiatives target women and confirm their position as principal guardians of health within the family are considered, as well as literature on the breast cancer awareness campaign. I then explore the growing body of literature on masculinity and health, and its account of the relationship between gender and current ideas about healthiness. Finally, I offer up some suggestions for the direction a new feminist critique of health might take.     

Quantifying uncertainty in the biospheric carbon flux for England and Wales

Summary.  A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO₂) concentrations in the atmosphere. Vegetation can extract CO₂ through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 10¹² g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.     

Risk management: a general framework for rural development

This paper proposes a new concept of rural development in an uncertain world. The nature of risk and uncertainty is discussed and risk management is defined as a positive model of economic and social behaviour. Some relevant paradigms for rural development are reviewed and evaluated within the general approach of risk management. It is demonstrated that the proposed view of risk management can effectively combine and reconcile different approaches by highlighting their advantages and shortcomings. Departing from a subjective definition of risk management, we progressively include its social dimensions which introduce both complexity and structure into the process of rural development.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Health technology assessment between our health care system and our health

In this contribution, I wish to explore the potential of health technology assessment and ethics for increasing our capacity to pre-empt the shortcomings and undesired consequences of modern health care while maintaining its benefits. Central is the presumption that in case of some health problems this cannot be done unless we explicitly reconsider some features of the modern health care system, especially those related to its strong reliance on scientific rationality and the strong role played by medical professionals. So as to both maintain the benefits of advanced health care and ensure that it produces less reason for concern, we need to reconsider our approach to rationality—and maybe even the way in which we build our health care system around that rationality. That is, we need to introduce an element of reflexivity. Two types of circumstances are being explored in which such reflexivity may prove worthwhile: controversies on side effects, and persistent problems encountered in optimising health care. Drawing on brief discussions of typical cases, we explore the potential of reflexive HTA and its methodical prerequisites. We conclude that ethicists may contribute to reflexive HTA, if they combine a hermeneutic—and often also participative—methodology with a solid understanding of the relation between the health problem under scrutiny and more general critique of the health care system. Insights from the areas of science and technology studies, as well as from social philosophy may be critical items in their tool kit.     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.