Bourdieu, Strategy, and Identity Work: A Case from a Manufacturing Organisation in Sri Lanka

This empirical study aims to discuss how organisational actors' identity work is reflected through their strategy work, from a Bourdieusian perspective. The study is a case study which followed the qualitative research approach. The participants of the study were managers representing a cross-section of a manufacturing organisation in Sri Lanka.  Twenty-six semi-structured interviews were used for the generation of the data for thematic analysis. NVivo12 data management software was used for the data management and in initial coding. It was found that managers are engaged in different identity work for self during their strategy work, in the implementation of a new organisational strategy. Further, the behaviour and practices normalised in the selected organisation through managers' strategy work reflected their identity work for other/s in way of defining other/s. The discussion was based on the theory of practice by Pierre Bourdieu (1990). Accordingly, this research shows how the identity work of position takers (newly joined and promoted organisational actors) supports shaping the practices linked with a new strategy (strategy work). Further, their identity work reflected through strategy work is also connected with their individual dispositions (habitus). The discussion further shows how individuals’ capital—mainly their cultural capital—contribute to constructing a new strategy in the selected organisational field. As implications of this study, it highlighted the contribution of the position-takers in shaping the organisation's strategy (strategy work) while engaging in identity work for self and others. Consequently, this study illustrates how organisational actors perform different social-symbolic work (identity work and strategy work) in parallel.  Keywords: Capital; Habitus, Identity work; Social-symbolic work; Strategy wor

Bayesian Analysis of Inflation III: Slow Roll Reconstruction Using Model Selection

We implement Slow Roll Reconstruction -- an optimal solution to the inverse problem for inflationary cosmology -- within ModeCode, a publicly available solver for the inflationary dynamics. We obtain up-to-date constraints on the reconstructed inflationary potential, derived from the WMAP 7-year dataset and South Pole Telescope observations, combined with large scale structure data derived from SDSS Data Release 7. Using ModeCode in conjunction with the MultiNest sampler, we compute Bayesian evidence for the reconstructed potential at each order in the truncated slow roll hierarchy. We find that the data are well-described by the first two slow roll parameters, \epsilon and \eta, and that there is no need to include a nontrivial \xi parameter.Comment: 14 pages, 12 figures, minor changes; final version; accepted in PR

Classification of Multiwavelength Transients with Machine Learning

With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will lead to a dramatic increase in data volume. Machine learning techniques are well suited to address this data challenge and rapidly classify newly detected transients. We present a multiwavelength classification algorithm consisting of three steps: (1) interpolation and augmentation of the data using Gaussian processes; (2) feature extraction using wavelets; and (3) classification with random forests. Augmentation provides improved performance at test time by balancing the classes and adding diversity into the training set. In the first application of machine learning to the classification of real radio transient data, we apply our technique to the Green Bank Interferometer and other radio light curves. We find we are able to accurately classify most of the 11 classes of radio variables and transients after just eight hours of observations, achieving an overall test accuracy of 78 percent. We fully investigate the impact of the small sample size of 82 publicly available light curves and use data augmentation techniques to mitigate the effect. We also show that on a significantly larger simulated representative training set that the algorithm achieves an overall accuracy of 97 percent, illustrating that the method is likely to provide excellent performance on future surveys. Finally, we demonstrate the effectiveness of simultaneous multiwavelength observations by showing how incorporating just one optical data point into the analysis improves the accuracy of the worst performing class by 19 percent.Comment: 16 pages, 12 figure

Quantifying the Rarity of the Local Super-Volume

We investigate the extent to which the number of clusters of mass exceeding 1015M⊙h−1 within the local super-volume (⁠<135Mpch−1⁠) is compatible with the standard ΛCDM cosmological model. Depending on the mass estimator used, we find that the observed number N of such massive structures can vary between 0 and 5. Adopting N = 5 yields ΛCDM likelihoods as low as 2.4 × 10−3 (with σ8 = 0.81) or 3.8 × 10−5 (with σ8 = 0.74). However, at the other extreme (N = 0), the likelihood is of order unity. Thus, while potentially very powerful, this method is currently limited by systematic uncertainties in cluster mass estimates. This motivates efforts to reduce these systematics with additional observations and improved modelling

Quantifying the Rarity of the Local Super-Volume

We investigate the extent to which the number of clusters of mass exceeding 1015M⊙h−1 within the local super-volume (⁠<135Mpch−1⁠) is compatible with the standard ΛCDM cosmological model. Depending on the mass estimator used, we find that the observed number N of such massive structures can vary between 0 and 5. Adopting N = 5 yields ΛCDM likelihoods as low as 2.4 × 10−3 (with σ8 = 0.81) or 3.8 × 10−5 (with σ8 = 0.74). However, at the other extreme (N = 0), the likelihood is of order unity. Thus, while potentially very powerful, this method is currently limited by systematic uncertainties in cluster mass estimates. This motivates efforts to reduce these systematics with additional observations and improved modelling

Cosmological Constraints on Dissipative Models of Inflation

(Abridged) We study dissipative inflation in the regime where the dissipative term takes a specific form, \Gamma=\Gamma(\phi), analyzing two models in the weak and strong dissipative regimes with a SUSY breaking potential. After developing intuition about the predictions from these models through analytic approximations, we compute the predicted cosmological observables through full numerical evolution of the equations of motion, relating the mass scale and scale of dissipation to the characteristic amplitude and shape of the primordial power spectrum. We then use Markov Chain Monte Carlo techniques to constrain a subset of the models with cosmological data from the cosmic microwave background (WMAP three-year data) and large scale structure (SDSS Luminous Red Galaxy power spectrum). We find that the posterior distributions of the dissipative parameters are highly non-Gaussian and their allowed ranges agree well with the expectations obtained using analytic approximations. In the weak regime, only the mass scale is tightly constrained; conversely, in the strong regime, only the dissipative coefficient is tightly constrained. A lower limit is seen on the inflation scale: a sub-Planckian inflaton is disfavoured by the data. In both weak and strong regimes, we reconstruct the limits on the primordial power spectrum and show that these models prefer a {\it red} spectrum, with no significant running of the index. We calculate the reheat temperature and show that the gravitino problem can be overcome with large dissipation, which in turn leads to large levels of non-Gaussianity: if dissipative inflation is to evade the gravitino problem, the predicted level of non-Gaussianity might be seen by the Planck satellite.Comment: 14 pages, 9 figures, Accepted by JCAP without text changes, References adde

Comparing Infrared Dirac-Born-Infeld Brane Inflation to Observations

We compare the Infrared Dirac-Born-Infeld (IR DBI) brane inflation model to observations using a Bayesian analysis. The current data cannot distinguish it from the \LambdaCDM model, but is able to give interesting constraints on various microscopic parameters including the mass of the brane moduli potential, the fundamental string scale, the charge or warp factor of throats, and the number of the mobile branes. We quantify some distinctive testable predictions with stringy signatures, such as the large non-Gaussianity, and the large, but regional, running of the spectral index. These results illustrate how we may be able to probe aspects of string theory using cosmological observations.Comment: 54 pages, 13 figures. v2: non-Gaussianity constraint has been applied to the model; parameter constraints have tightened significantly, conclusions unchanged. References added; v3, minor revision, PRD versio

First Observational Tests of Eternal Inflation: Analysis Methods and WMAP 7-Year Results

In the picture of eternal inflation, our observable universe resides inside a single bubble nucleated from an inflating false vacuum. Many of the theories giving rise to eternal inflation predict that we have causal access to collisions with other bubble universes, providing an opportunity to confront these theories with observation. We present the results from the first observational search for the effects of bubble collisions, using cosmic microwave background data from the WMAP satellite. Our search targets a generic set of properties associated with a bubble collision spacetime, which we describe in detail. We use a modular algorithm that is designed to avoid a posteriori selection effects, automatically picking out the most promising signals, performing a search for causal boundaries, and conducting a full Bayesian parameter estimation and model selection analysis. We outline each component of this algorithm, describing its response to simulated CMB skies with and without bubble collisions. Comparing the results for simulated bubble collisions to the results from an analysis of the WMAP 7-year data, we rule out bubble collisions over a range of parameter space. Our model selection results based on WMAP 7-year data do not warrant augmenting LCDM with bubble collisions. Data from the Planck satellite can be used to more definitively test the bubble collision hypothesis.Comment: Companion to arXiv:1012.1995. 41 pages, 23 figures. v2: replaced with version accepted by PRD. Significant extensions to the Bayesian pipeline to do the full-sky non-Gaussian source detection problem (previously restricted to patches). Note that this has changed the normalization of evidence values reported previously, as full-sky priors are now employed, but the conclusions remain unchange

New Solutions of the Inflationary Flow Equations

The inflationary flow equations are a frequently used method of surveying the space of inflationary models. In these applications the infinite hierarchy of differential equations is truncated in a way which has been shown to be equivalent to restricting the set of models considered to those characterized by polynomial inflaton potentials. This paper explores a different method of solving the flow equations, which does not truncate the hierarchy and in consequence covers a much wider class of models while retaining the practical usability of the standard approach.Comment: References added, and a couple of comment