Can Ideas be Capital? Factors of Production in the Post-Industrial Economy: A Review and Critique

Economic and social relations are undergoing radical change, expressed in such concepts as “knowledge economy,” “weightless economy,” “postindustrial society,” and “information society.” The literature suggests the arrival of a distinct new factor of production—intellectual capital—replacing or perhaps supplementing land, labor, and capital. We give a historically informed theoretical exposition of capital as the durable result of past production processes, transforming future production while not being transformed itself and associated with a particular economic actor. We then construct a taxonomy of the possible characteristics and location of intellectual capital in postindustrial production

Delivering ‘Effortless Experience’ Across Borders: Managing Internal Consistency in Professional Service Firms

This article explores how professional service firms manage across borders. When clients require consistent services delivered across multiple locations, especially across borders, then firms need to develop an organization that is sufficiently flexible to be able to support such consistent service delivery. Our discussion is illustrated by the globalization process of law firms. We argue that the globalization of large corporate law firms primarily takes place in terms of investments in the development of protocols, processes and practices that enhance internal consistency such that clients receive an ‘effortless experience’ of the service across multiple locations worldwide. Over the longer term the ability to deliver such effortless experience is dependent upon meaningful integration within and across the firm. Firms that achieve this are building a source of sustainable competitive advantage

Funding Mechanisms, Cost Drivers, and the Distribution of Education Funds in Alberta: A Case Study

This article examines the impact that the 1994 funding changes introduced by the Alberta government have had on the Calgary Board of Education (CBE)—the largest urban board in Alberta and one of the largest boards in Canada. Starting from a critical financial analysis perspective we ather, examine, and recalculate key historical financial data pertaining to the CBE, contextualizing these data through the use of supplementary nonfinancial archival materials. Our analysis highlights the impact that funding changes have had on the CBE, but also indirectly tells us something about the impact on other school boards in the province, because the total amount of per-student education funding has remained relatively constant. More generally, the analysis illustrates how funding mechanisms can be and are used to govern from a distance and how seemingly neutral accounting/funding techniques function to distribute resources among different school boards. By drawing attention to these distributional effects, the current study makes visible the power of largely invisible funding mechanisms in the sphere of public education.Cet article traite de l'impact qu'ont eu les modifications de financement, introduites par le gouvernement de l’Alberta en 1994, sur le Calgary Board of Education (CBE), une des commissions scolaires urbaines les plus importantes de la province et une des commissions scolaires les plus importantes au Canada. S'appuyant sur une perspective d'analyse financière critique, les auteurs recueillent, étudient et recalculent les principales données financières qui ont touché le CBE en les contextualisant par l'apport d'informations d'archives de nature non-financière. L'analyse fait ressortir l'impact des modifications de financement sur le CBE et, puisque les subventions globales par élève ont demeuré relativement constantes, elle fournit indirectement des renseignements quant à l'impact sur les autres conseils scolaires de la province. De façon plus générale, l'analyse démontre la façon dont on se sert de mécanismes de financement pour gouverner à distance et explique le fonctionnement des stratégies de financement, en apparence neutres, dans la distribution de ressources parmi différents conseils scolaires. En mettant ces effets de distribution en relief, cette recherche rend évident le pouvoir des mécanismes de financement en grande partie invisibles dans le domaine de l'éducation publique

Does Wheat Cultivar Choice Affect Crop Quality and Soil Microbial Communities in Cropping Systems?

Wheat (Triticum aestivum L.) cultivars may have differential effects on soil microbial communities and the breadmaking quality of harvested grain. We compared six Canadian spring wheat cultivars under organic and conventional management systems for yield, breadmaking quality and soil phospholipid fatty acid analysis (PLFA) profile. Yields were lower, but protein levels were higher in the organic system. Cultivars differed for quality traits, but all cultivars had acceptable levels for processing. There were small differences in PLFA profiles for cultivars in the conventional system, but none in the organic system. More significant correlations between grain quality and PLFA measures were present in the organic system. Protein levels and breadmaking quality at least equal to conventional systems can be achieved in organic systems. Wheat cultivars differed for grain quality in both organic and conventional systems, and culivars altered the soil microbial profile in conventional systems. Microbes may play a greater role in determining crop quality in organic systems than in conventional systems

Exit, Voice, Loyalty and Neglect as Student Responses to Dissatisfaction: An Act Frequency Approach

An important task in higher education is the provision of an abstract theoretical model capable of integrating various student responses to dissatisfaction. Drawing upon recent work in the social sciences, we propose exit, voice, loyalty and neglect (EVLN) as a parsimonious means of understanding the relationships among the different responses to dissatisfaction. We use an act frequency approach to develop and validate the EVLN constructs as a preliminary first step toward future predictive theory.La définition d'un modèle théorique abstrait capable d'intégrer les différentes réactions de mécontentement des étudiants est une tâche importante dans le domaine de l'enseignement supérieur. En nous appuyant sur des recherches récentes en sciences sociales, nous proposons "sortie, voix, loyauté et manque d'attention" comme moyen parcimonieux pour comprendre les relations entre les différentes réactions de mécontentement. Nous utilisons une approche de fréquence d'actions pour élaborer et valider les concepts de "sortie, voix, loyauté et manque d'attention", ce qui constitue un premier pas vers une théorie prédictive future

Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks

In this paper, we describe how a patient-specific, ultrasound-probe-induced prostate motion model can be directly generated from a single preoperative MR image. Our motion model allows for sampling from the conditional distribution of dense displacement fields, is encoded by a generative neural network conditioned on a medical image, and accepts random noise as additional input. The generative network is trained by a minimax optimisation with a second discriminative neural network, tasked to distinguish generated samples from training motion data. In this work, we propose that 1) jointly optimising a third conditioning neural network that pre-processes the input image, can effectively extract patient-specific features for conditioning; and 2) combining multiple generative models trained separately with heuristically pre-disjointed training data sets can adequately mitigate the problem of mode collapse. Trained with diagnostic T2-weighted MR images from 143 real patients and 73,216 3D dense displacement fields from finite element simulations of intraoperative prostate motion due to transrectal ultrasound probe pressure, the proposed models produced physically-plausible patient-specific motion of prostate glands. The ability to capture biomechanically simulated motion was evaluated using two errors representing generalisability and specificity of the model. The median values, calculated from a 10-fold cross-validation, were 2.8+/-0.3 mm and 1.7+/-0.1 mm, respectively. We conclude that the introduced approach demonstrates the feasibility of applying state-of-the-art machine learning algorithms to generate organ motion models from patient images, and shows significant promise for future research.Comment: Accepted to MICCAI 201

Adversarial Deformation Regularization for Training Image Registration Neural Networks

We describe an adversarial learning approach to constrain convolutional neural network training for image registration, replacing heuristic smoothness measures of displacement fields often used in these tasks. Using minimally-invasive prostate cancer intervention as an example application, we demonstrate the feasibility of utilizing biomechanical simulations to regularize a weakly-supervised anatomical-label-driven registration network for aligning pre-procedural magnetic resonance (MR) and 3D intra-procedural transrectal ultrasound (TRUS) images. A discriminator network is optimized to distinguish the registration-predicted displacement fields from the motion data simulated by finite element analysis. During training, the registration network simultaneously aims to maximize similarity between anatomical labels that drives image alignment and to minimize an adversarial generator loss that measures divergence between the predicted- and simulated deformation. The end-to-end trained network enables efficient and fully-automated registration that only requires an MR and TRUS image pair as input, without anatomical labels or simulated data during inference. 108 pairs of labelled MR and TRUS images from 76 prostate cancer patients and 71,500 nonlinear finite-element simulations from 143 different patients were used for this study. We show that, with only gland segmentation as training labels, the proposed method can help predict physically plausible deformation without any other smoothness penalty. Based on cross-validation experiments using 834 pairs of independent validation landmarks, the proposed adversarial-regularized registration achieved a target registration error of 6.3 mm that is significantly lower than those from several other regularization methods.Comment: Accepted to MICCAI 201

An evaluation of a violence reduction partnership network:mixed methods network analysis

Purpose: The purpose of this paper was to report on the evaluation of the network and resources for violence prevention and reduction in the chosen area of focus. This area had experiences deprivation, significant implications due to Covid-19 restrictions and a lack of outdoor recreation space. Design/methodology/approach: Network analysis methodologies are increasingly being used in criminological research and evaluations to assess the structures of social and economic networks. This study explored, using a mixed-methods network analysis methodology, the nature of the established violence reduction network in a specific geographical location in West Midlands. Findings: A breadth of network activity is taking place across the community; however, the network analysis highlighted gaps in terms of specialist provision for early years and support from those with lived experience. It was perceived that a lack of continuity, in terms of changes in key roles, has affected the network. Funding mechanisms were perceived ineffective, and not encouraging of development of localisation services. Relationships between network members were predominantly positive with organisations having good communication and accessing support from one another; however, identifying shared goals and better collective working would benefit the network. Originality/value: This study pioneers using an innovative, mixed methods network analysis to explore a public health approach to violence prevention and reduction. Quantitative data collection and analysis allowed for assessment of the networks capacity and density, whereas qualitative data provided insights and detailed accounts of how the network functions.</p