The Interplay of Experience and Social Structure: Adaptation through Media

In this investigation, I explore the tensions which self-referentially emerge within our constructed ‘nature’. I begin by exploring the origins of our contemporary media environment as discussed by McLuhan. I then interrogate the challenges of digital life through a close reading of the work of technology critic Giles Slade. I then conclude by situating these seemingly competing views of mediated existence within the framework of social systems theory. Through the lens of social systems theory, I reframe our contemporary technologies as adaptations to past challenges which also shape our experience of the potential choices and challenges of the future

A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.

A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r (16) > 0.626, p < 0.03 corrected], global efficiency [r (16) > 0.601, p < 0.04 corrected], and mean clustering coefficient [r (16) > 0.625, p < 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r (16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F (4, 135) = 113.546, p < 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control

Low zinc status and absorption exist in infants with jejunostomies or ileostomies which persists after intestinal repair.

There is very little data regarding trace mineral nutrition in infants with small intestinal ostomies. Here we evaluated 14 infants with jejunal or ileal ostomies to measure their zinc absorption and retention and biochemical zinc and copper status. Zinc absorption was measured using a dual-tracer stable isotope technique at two different time points when possible. The first study was conducted when the subject was receiving maximal tolerated feeds enterally while the ostomy remained in place. A second study was performed as soon as feasible after full feeds were achieved after intestinal repair. We found biochemical evidence of deficiencies of both zinc and copper in infants with small intestinal ostomies at both time points. Fractional zinc absorption with an ostomy in place was 10.9% ± 5.3%. After reanastamosis, fractional zinc absorption was 9.4% ± 5.7%. Net zinc balance was negative prior to reanastamosis. In conclusion, our data demonstrate that infants with a jejunostomy or ileostomy are at high risk for zinc and copper deficiency before and after intestinal reanastamosis. Additional supplementation, especially of zinc, should be considered during this time period

Invitation to the Table Conversation: A Few Diverse Perspectives on Integration

This article represents an invitation to the integration table to several previously underrepresented perspectives within Christian psychology. The Judeo-Christian tradition and current views on scholarship and Christian faith compel us to extend hospitality to minority voices within integration, thereby enriching and challenging existing paradigms in the field. Contributors to this article, spanning areas of cultural, disciplinary, and theological diversity, provide suggestions for how their distinct voices can enhance future integrative efforts

Do Social Movements Spur Corporate Change? The Rise of “MeToo Termination Rights” in CEO Contracts

Do social movements spur corporate change? This Article sheds new empirical and theoretical light on the issue through an original study of executive contracts before and after MeToo. The MeToo movement, beginning in late 2017, exposed a workplace culture seemingly permissive of high-level, sex-based misconduct. Companies typically responded slowly and imposed few consequences on perpetrators, often allowing them to depart with lucrative exit packages. Why did companies reward rather than penalize bad actors, and has the movement disrupted this culture of complicity? The passage of time since the height of the movement allows us to investigate these issues empirically, using the lens of executive contracts. Economic theory posits that CEO employment agreements are not negotiated at arm’s length and contain terms that strongly favor the executive. We hypothesize that these dynamics—typically associated with outsized compensation packages—resulted in pro-executive termination provisions that left room for executives to engage in sexbased misconduct without fear of reprisal. We argue that the MeToo movement represented a major shock to these bargaining dynamics and predict that, in the face of new reputational and liability risks, corporate boards will seek to reserve greater power to terminate CEOs for sex-based misconduct in post-MeToo agreements. We test—and substantiate—our hypotheses using a novel dataset of CEO employment agreements. We focus on changes to the contractual definition of a “forcause” termination. In the wake of MeToo, we find a significant and growing rise in the prevalence of what we call “MeToo termination rights”—definitions of cause that permit companies to terminate CEOs without severance pay in cases of harassment, discrimination, and violations of company policy. Such grounds for cause broadly capture most forms of sex-based misconduct. This documented rise in “MeToo termination rights” holds important lessons for corporate governance, executive contracting, and gender equity. First, our results show that external shocks can disrupt traditional corporate bargaining dynamics, bringing contract terms more in line with changing expectations. Second, our results provide insight into contract design, suggesting possible tradeoffs that companies make in structuring these novel termination rights. Finally, our results can be understood as reflecting a realignment of the treatment of top-level executives with the treatment of ordinary workers, who have long been subject to capacious sexual harassment policies. We conclude that the rise in “MeToo termination rights” offers evidence of increased corporate control of CEO behavior and greater institutional accountability for sex-based misconduct. We are therefore cautiously optimistic about the long-term effects of MeToo and the ability of powerful social movements to inspire change within private institutions

Meta-learning with implicit gradients in a few-shot setting for medical image segmentation

Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general application of any trained model is quite limited for medical imaging for clinical practice. Using separately trained models for each unique lesion category or a unique patient population will require sufficiently large curated datasets, which is not practical to use in a real-world clinical set-up. Few-shot learning approaches can not only minimize the need for an enormous number of reliable ground truth labels that are labour-intensive and expensive, but can also be used to model on a dataset coming from a new population. To this end, we propose to exploit an optimization-based implicit model agnostic meta-learning (iMAML) algorithm under few-shot settings for medical image segmentation. Our approach can leverage the learned weights from diverse but small training samples to perform analysis on unseen datasets with high accuracy. We show that, unlike classical few-shot learning approaches, our method improves generalization capability. To our knowledge, this is the first work that exploits iMAML for medical image segmentation and explores the strength of the model on scenarios such as meta-training on unique and mixed instances of lesion datasets. Our quantitative results on publicly available skin and polyp datasets show that the proposed method outperforms the naive supervised baseline model and two recent few-shot segmentation approaches by large margins. In addition, our iMAML approach shows an improvement of 2%–4% in dice score compared to its counterpart MAML for most experiments