The construction of a taxonomy of early childhood educators’ work

Despite considerable research on the impact of early childhood education (ECE), there is little empirical evidence about what the everyday work of educators entails. This paper reports on the development of a tool to capture generalisable data on the everyday work of educators so as to inform effective workforce policy. This tool—a taxonomy of early childhood educators’ work—was developed by drawing on the expertise of six early years’ experts from Australia and the United States of America (USA) and includes time-use diaries, focus groups and interviews with 21 early childhood educators working in long day care and preschool services. The taxonomy, which we present here, consists of 10 domains, each with a number of sub-classes. We propose that this taxonomy is a useful codification system for ascertaining the everyday work tasks, activities and actions of early childhood educators in diverse early years’ settings. It is anticipated that the taxonomy will prove a valuable tool for subsequent research investigating the early childhood workforce.

Measuring tax efficiency: A tax optimality index

This paper introduces an index of tax optimality that measures the distance of some current tax structure from the optimal tax structure in the presence of public goods. This index is defined on the [0, 1] interval and measures the proportion of the optimal tax rates that will achieve the same welfare outcome as some arbitrarily given initial tax structure. We call this number the Tax Optimality Index. We also show how the basic methodology can be altered to derive a revenue equivalent uniform tax, which measures the tax burden implied by the public sector. A numerical example is used to illustrate the method developed, and extensions of the analysis to handle models with multiple households and nonlinear taxation structures are undertaken.

Osteoporosis medication dispensing for older Australian women from 2002 to 2010: Influences of publications, guidelines, marketing activities and policy

Purpose Developments in anti-osteoporosis medications (AOMs) have led to changes in guidelines and policy, which, along with media and marketing strategies, have had an impact upon the prescribing of AOM. The aim was to examine patterns of AOM dispensing in older women (aged 76–81 years at baseline) from 2002 to 2010. Methods Administrative claims data were used to describe AOM dispensing in 4649 participants (born in 1921–1926 and still alive in 2011) in the Australian Longitudinal Study on Women's Health. The patterns were interpreted in the context of changes in guidelines, indications for subsidy, publications (scholarly and general media), and marketing activities. Results Total use of AOM increased from 134 DDD/1000/day in 2002 to 216 DDD/1000/day in 2007 but then decreased to 184 DDD/1000/day in 2010. Alendronate was the most commonly dispensed AOM but decreased from 2007, while use of risedronate (2002 onward), strontium ranelate (2007 onward) and zoledronic acid (2008 onward) increased. Etidronate and hormone replacement therapy (HRT) prescriptions gradually decreased over time. The decline in alendronate dispensing coincided with increases of other bisphosphonates and publicity about potential adverse effects of bisphosphonates, despite relaxing indications for bone density testing and subsidy for AOM. Conclusions Overall dispense of AOM from 2002 reached a peak in 2007 and thereafter declined despite increases in therapeutic options and improved subsidised access. The recent decline in overall AOM dispensing seems to be explained largely by negative publicity rather than specific changes in guidelines and policy.

Long-term effects of physical activity level on changes in healthy body mass index over 12 years in young adult women

Objectives To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. Patients and Methods Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. Results In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. Conclusion These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.

Do SMEs cluster around innovation activities? Discovering active, incremental and opportunistic innovators

Do SMEs cluster around different types of innovation activities? Are there patterns of SME innovation activities? To investigate we develop a taxonomy of innovation activities in SMEs using a qualitative study, followed by a survey. First, based upon our qualitative research and literature review we develop a comprehensive list of innovation activities SMEs typically engage in. We then conduct a factor analysis to determine if these activities can be combined into factors. We identify three innovation activity factors: R&D activities, incremental innovation activities and cost innovation activities. We use these factors to identify three clusters of firms engaging in similar innovation activities: active innovators, incremental innovators and opportunistic innovators. The clusters are enriched by validating that they also exhibit significant internal similarities and external differences in their innovation skills, demographics, industry segments and family business ownership. This research contributes to innovation and SME theory and practice by identifying SME clusters based upon their innovation activities.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.