Barriers to women in the UK construction industry

Purpose – This paper aims to identify the main barriers that lead to the under-representation of women in the UK construction industry. The study, funded by ConstructionSkills, seeks to explore the issues that women face and investigate the potential positive impact that continuous professional development (CPD) may have upon improving the retention and career progression of women. Design/methodology/approach – The study uses an open-ended grounded theory (GT) approach, including 231 semi-structured questionnaires and nine focus groups with women from a range of professional occupations. All the findings were analysed using keyword analysis to identify the top two barriers that women face, alongside a series of cross-cutting key themes and issues. Findings – The findings reveal that male-dominated organisational cultures and inflexible working practices are the main barriers to women in the UK construction industry, irrespective of job role or profession. This paper concludes by arguing for a sea-change in the expansion of CPD opportunities for women in managerial, confidence and communication based skills, with accompanying networking and support systems to facilitate the retention and advancement of women in the industry sector. Research limitations/implications – Due to the research approach, the data are not generalisable. Therefore, researchers are advised to research and test the findings with a larger group. Researchers are also recommended to investigate the impact of expanded CPD opportunities for both men and women. Originality/value – The paper puts forward a business case for the advancement of specific CPD training for women, to facilitate the expansion of equality and diversity in the workforce in the UK construction industry

Contraction of the G_r,s Quantum Group to its Nonstandard analogue and corresponding Coloured Quantum Groups

The quantum group G_r,s provides a realisation of the two parameter quantum GL_p,q(2) which is known to be related to the two parameter nonstandard GL_hh'(2) group via a contraction method. We apply the contraction procedure to G_r,s and obtain a new Jordanian quantum group G_m,k. Furthermore, we provide a realisation of GL_h,h'(2) in terms of G_m,k. The contraction procedure is then extended to the coloured quantum group GL_r{\lambda,\mu}(2) to yield a new Jordanian quantum group GL_m{\lambda,\mu}(2). Both G_r,s and G_m,k are then generalised to their coloured versions which inturn provide similar realisations of GL_r{\lambda,\mu}(2) and GL_m{\lambda,\mu}(2).Comment: 22 pages LaTeX, to be published in J. Math. Phy

Learning physics in context: a study of student learning about electricity and magnetism

This paper re-centres the discussion of student learning in physics to focus on context. In order to do so, a theoretically-motivated understanding of context is developed. Given a well-defined notion of context, data from a novel university class in electricity and magnetism are analyzed to demonstrate the central and inextricable role of context in student learning. This work sits within a broader effort to create and analyze environments which support student learning in the sciencesComment: 36 pages, 4 Figure

Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits

The color of milk affects the subsequent color features of the resulting dairy products; milk color is also related to milk fat concentration. The objective of the present study was to quantify the ability of mid-infrared spectroscopy (MIRS) to predict color-related traits in milk samples and to estimate the correlations between these color-related characteristics and traditional milk quality traits. Mid-infrared spectral data were available on 601 milk samples from 529 cows, all of which had corresponding gold standard milk color measures determined using a Chroma Meter (Konica Minolta Sensing Europe, Nieuwegein, the Netherlands); milk color was expressed using the CIELAB uniform color space. Separate prediction equations were developed for each of the 3 color parameters (L* = lightness, a* = greenness, b* = yellowness) using partial least squares regression. Accuracy of prediction was determined using both cross validation on a calibration data set (n = 422 to 457 samples) and external validation on a data set of 144 to 152 samples. Moderate accuracy of prediction was achieved for the b* index (coefficient of correlation for external validation = 0.72), although poor predictive ability was obtained for both a* and L* indices (coefficient of correlation for external validation of 0.30 and 0.55, respectively). The linear regression coefficient of the gold standard values on the respective MIRS-predicted values of a*, L*, and b* was 0.81, 0.88, and 0.96, respectively; only the regression coefficient on L* was different from 1. The mean bias of prediction (i.e., the average difference between the MIRS-predicted values and gold standard values in external validation) was not different from zero for any of 3 parameters evaluated. A moderate correlation (0.56) existed between the MIRS-predicted L* and b* indices, both of which were weakly correlated with the a* index. Milk fat, protein, and casein were moderately correlated with both the gold standard and MIRS-predicted values for b*. Results from the present study indicate that MIRS data provides an efficient, low-cost screening method to determine the b* color of milk at a population level

Employing community data to investigate social and structural dimensions of urban neighborhoods: An early childhood education example

The present study sought to define neighborhood context by examining relationships among data from city-level administrative databases at the level of the census block group. The present neighborhood investigation included 1,801 block groups comprising a large, northeastern metropolitan area. Common factor analyses and multistage, hierarchical cluster analyses yielded two dimensions (i.e., Social Stress, Structural Danger) and two typologies (i.e., Racial Composition, Property Structure Composition) of neighborhood context. Simultaneous multiple regression analyses revealed small but statistically significant associations between neighborhood variables and academic outcomes for public school kindergarten children