Structuring institutional analysis for urban ecosystems: A key to sustainable urban forest management

A decline in urban forest structure and function in the United States jeopardizes the current focus on developing sustainable cities. A number of social dilemmas—for example, free-rider problems—restrict the sustainable production of ecosystem services and the stock of urban trees from which they flow. However, institutions, or the rules, norms, and strategies that affect human decision-making, resolve many such social dilemmas, and thus, institutional analysis is imperative for understanding urban forest management outcomes. Unfortunately, we find that the definition of institutions varies greatly across and within disciplines, and conceptual frameworks in urban forest management and urban ecosystems research often embed institutions as minor variables. Given the significance of institutional analysis to understanding sustainable rural resource management, this paper attempts to bring clarity to defining, conceptually framing, and operationally analyzing institutions in urban settings with a specific focus on sustainable urban forest management. We conclude that urban ecologists and urban forest management researchers could benefit from applying a working definition of institutions that uniquely defines rules, norms, and strategies, by recognizing the nested nature of operational, collective choice, and constitutional institutions, and by applying the Institutional Analysis and Development framework for analysis of urban social-ecological systems (SESs). Such work promises to spur the desired policy-based research agenda of urban forestry and urban ecology and provide cross-disciplinary fertilization of institutional analysis between rural SESs and urban ecosystems.     

The health of health care organizations

Abstract

This paper explores the nature and development of health care organizations in terms of a model of organizational healthiness. The model places particular emphasis on the psychosocial subsystems which describe the subjective organization. These represent the perceived internal functioning of the organization in terms of task completion, problem solving and staff development. The implications of such a model for the well-being of health care staff and for the evaluation of service delivery are discussed.     

Logistic regression and latent class models for estimating positivities in diagnostic assays with poor resolution

In biomedical research and diagnostic practice it is common to classify objects dichotomously based on continuous observations (x) measuring some form of biological activity, where some proportion of the objects have a level of activity above background. In this paper, we consider the problem of estimating the proportion of positive objects for a typical assay where:(i) the distribution of x for positive objects is unknown. although (ii) the risk of positivity is known to be a monotonic function of x:and (iii) x has been measured for a set of negative control objects. Monte Carlo simulations evaluating four alternative estimators of the positivity, including novel non-parametric mixture decompositions, indicate that where the positives and negatives have distributions of x with a moderate degree of overlap, a non-parametric decomposition using a latent class model provides precise and close to unbiased estimates. The methods are illustrated using data from an autoradiography assay used in cell biology.     

Holding the Traveller's Gaze Accountable in Shiva Naipaul's North of South: An African Journey

Abstract

Travelogues are partly based on what is witnessed, observed and noted about the places and people visited and what is already known in advance, mainly from an existing archive. The archive, therefore, is an important element in travel writing. However, an author cannot avoid responsibility for what she/he notes/writes/composes about a place and its people. In a sense, a biography of a place may represent a writer's struggles to compromise between the material in the archive – such as existing books on the subject of his/her writing – and what she/he actually observed/observes. The veracity of the writer's narrative/story is dependent on the logic of the evidence that he/she adduces. The weight of the archived narrative, however, can burden the writer in which case he/she would need to limit its influence in order to tell a ‘believable’ story. Shiva Naipaul's extensive reliance on the existing pre- and colonial-time archive of writing on Africa seriously undermines his representation of life in postcolonial East Africa. The result is a travelogue filled with a great sense of personal disappointment with the political, cultural, economic and social conditions in postcolonial Kenya, Tanzania and Zambia – the countries that he visits. Shiva seems to unwittingly translate this sense of deep disappointment into a ‘demonisation’ of Eastern Africa. Whilst acknowledging that there is a difference – and an important one – between a text and the world that it seeks to represent, the key proposition in this paper is that Naipaul's biography does not offer any redemptive characterisation of both the African space and the people that he writes about precisely because it summons a biased archive as evidence for its own claims.     

‘A mockery of equality’: an exploratory investigation into disabled activists’ views of the Paralympic Games

This article offers an exploratory analysis of the opinions of disabled activists towards the Paralympic Games. With the use of a qualitative online survey, the work focuses on the perceptions of disabled individuals (n = 32) who are not Paralympic athletes but are affiliated to the disability rights group, the United Kingdom Disabled People’s Council. Working on the premise that the views of disabled activists have been excluded from Paralympic sports discourse to date, the results illustrate a nuanced yet negative view of the Games to contrast with an existing, yet overly positive, academic narrative. Participants were particularly cynical of the portrayal and production of the Games and its Paralympic athletes as they perceived that the wider population of disabled people is misrepresented. The overwhelming perception in this preliminary analysis suggests that the Paralympic Games can be counterproductive to disability rights beyond sport.     

Estimation of proportions and ratios from line transect data

If the population of interest in a line transect survey consists of distinct sub-populations, or classes, line transect data can be used to estimate the proportion of the population in each class, or the ratio of the number of individuals in one class to another class. However, if the various classes have unequal overall detectability then the observed ratio or proportion is biased and should be adjusted. Estimators for the desired proportions and ratios are proposed and studied, and procedures for examining the equal detectability hypotheses are discussed.     

Partially pooled covariance matrix estimation in discriminant analysis

The Linear Discriminant Rule (LD) is theoretically justified for use in classification when the population within-groups covariance matrices are equal, something rarely known in practice. As an alternative, the Quadratic Discriminant Rule (QD) avoids assuming equal covariance matrices, but requires the estimation of a large number of parameters. Hence, the performance of QD may be poor if the training set sizes are small or moderate. In fact, simulation studies have shown that in the two-groups case LD often outperforms QD for small training sets even when the within -groups covariance matrices differ substantially. The present article shows this to be true when there are more than two groups, as well. Thus, it would seem reasonable and useful to develop a data-based method of classification that, in effect, represents a compromise between QD and LD. In this article we develop such a method based on an empirical Bayes formulation in which the within-groups covariance matrices are assumed to be outcomes of a common prior distribution whose parameters are estimated from the data. Two classification rules are developed under this framework and, through the use of extensive simulations, are compared to existing methods when the number of groups is moderate.