Creating and retaining authenticity among craft breweries: a case study of local breweries in Boston, Massachusetts

Brewing has a long history in this country--first making an appearance in 1620 with the landing of the Pilgrims at Plymouth Rock in Massachusetts. Today, beers can be easily categorized into one of two types: 1) industrial, and 2) craft. The focus of this paper is on this second type, the "craft beer" and the so-called "renaissance" it experienced during the 1980s. In 1983, there were only 43 operating breweries in the United States--today there are over 3,000 (Brewers Association, 2014). The resource- partitioning model, established within the organizational ecology field, has been used to explain this rapid growth (Carol & Swaminathan, 2000). However, of particular interest to me, are the reasons for why craft breweries are so appealing to consumers. Pulling from literatures in Urban, Cultural, and Economic Sociology, I argue that the key characteristic that has allowed craft breweries to experience such success is their apparent "authenticity" (Zukin, 2010; Brown-Saracino, 2007; Peterson & Anand, 2004; Sherman, 2007). To date, the majority of analyses focused on "authenticity" have centered its creation within the realm of production (Johnston & Baumann, 2007). It is true that craft breweries cultivate a sense of "authenticity" based on their location, as well as the well curated image they project within their own space. However, I argue that it is through the consumption experience, in which both producers and consumers play a crucial role, that craft breweries are able to further cultivate this "authentic" image, as well as hold onto it (Jones et al., 2005; Sherman, 2007). The idea that "authenticity" is not only found within the realm of production, but also consumption (such as at coffee shops and restaurants), has been explored by sociologists such as Richard Lloyd and Sharon Zukin (Lloyd, 2006; Zukin, 2011). It is my intent to explore the ways in which this is the case at breweries, as well as the variables, such as space and place, that contribute to the experience of "authenticity.

A Unique Methodology For Implementing High School Capstone Experiences Through Teacher Professional Development

Innovators and abstract thinkers - students who question why are going to be the future of engineering, of science and cures for diseases. Rarely do students ask where and how innovation is created. Students, particularly post-secondary students have lost their curiosity and they have lost their ability to question. Why? Because the relationship between theory and application has been removed from our high schools. Although the term “STEM” is generally used, students do not appear to understand the importance of core STEM principles such as Newton’s 2nd law and therefore do not understand the influence these basic algorithms have in daily life. In recent decades, high school education has focused on quizzes and exams, state and national standardize testing and SATs. More emphasis is placed on performing well on these exams, focusing on memorization and test taking rather than on thorough comprehension. The question is, “how do you translate theory to application in the high school classroom?” Students’ knowledge and engagement are only as good as their teachers. Educators need to be given the proper tools, resources, and knowledge. CAPSULE, a capstone-based experience provides tools, resources, and knowledge to enhance the teaching and learning involvement. CAPSULE teaches and promotes inquiry, exploration and application rather than just theory. The methodology engages and educates hands-on learning, teamwork and multiple solutions through the engineering design process (EDP). The theory behind innovation is the motivation for CAPSULE – to teach and engage teachers using 3D modeling, EDP, and project-based learning to create a high school capstone experience. This paper presents a new approach of teaching STEM related courses to high school students. The methodology presented is on “training the trainer” to enable and empower teachers to master and utilize this new approach.

ER exit in physiology and disease

The biosynthetic secretory pathway is comprised of multiple steps, modifications and interactions that form a highly precise pathway of protein trafficking and secretion, that is essential for eukaryotic life. The general outline of this pathway is understood, however the specific mechanisms are still unclear. In the last 15 years there have been vast advancements in technology that enable us to advance our understanding of this complex and subtle pathway. Therefore, based on the strong foundation of work performed over the last 40 years, we can now build another level of understanding, using the new technologies available. The biosynthetic secretory pathway is a high precision process, that involves a number of tightly regulated steps: Protein folding and quality control, cargo selection for Endoplasmic Reticulum (ER) exit, Golgi trafficking, sorting and secretion. When deregulated it causes severe diseases that here we categorise into three main groups of aberrant secretion: decreased, excess and altered secretion. Each of these categories disrupts organ homeostasis differently, effecting extracellular matrix composition, changing signalling events, or damaging the secretory cells due to aberrant intracellular accumulation of secretory proteins. Diseases of aberrant secretion are very common, but despite this, there are few effective therapies. Here we describe ER exit sites (ERES) as key hubs for regulation of the secretory pathway, protein quality control and an integratory hub for signalling within the cell. This review also describes the challenges that will be faced in developing effective therapies, due to the specificity required of potential drug candidates and the crucial need to respect the fine equilibrium of the pathway. The development of novel tools is moving forward, and we can also use these tools to build our understanding of the acute regulation of ERES and protein trafficking. Here we review ERES regulation in context as a therapeutic strategy

Research with schools on the early implementation of Curriculum for Wales: Wave 1 report

This report presents research conducted with schools on the early implementation of Curriculum for Wales. The research aims to undertake two waves of qualitative research during academic year 2022/23 to understand how the curriculum and assessment reforms are working for practitioners and learners in schools and settings, and the barriers and facilitators to successful implementation. The research informs the support that the Welsh Government and its partners are putting in place to maximise success. This report contains the findings of the first wave of qualitative research with 64 senior leaders in schools and Pupil Referral Units carried out on behalf of the Welsh Government between November 2022 to January 2023. A report detailing findings of a second wave of interviews with senior leaders, as well as fieldwork with learners, will be published later in 2023

Research on the early implementation of Curriculum for Wales: Wave 2 report

This report presents findings of the second wave (Wave 2) of qualitative research with 62 senior leaders in schools and Pupil Referral Units (PRUs) carried out by Arad Research and the Open University in Wales. The aim of this research was to undertake two waves of qualitative research during academic year 2022/23 to understand how the curriculum and assessment reforms were working for practitioners and learners in schools and settings, and the barriers and facilitators to successful implementation. This report follows on from the Wave 1 report, which presented findings of the first round of interviews with senior leaders. In addition to presenting findings from follow-up interviews with senior leaders, it also presents evidence from fieldwork with groups of learners in primary and secondary schools, outlining their experiences of curriculum delivery during the academic year 2022/23

L&D professionals in organisations: much ambition, unfilled promise

This monograph reports a study investigating the roles of learning and development (L&D) professionals in Irish, UK European and US organisations. The study investigates the contextual factors influencing L&D roles in organisations, the strategic and operational roles that L&D professionals play in organisations, the competencies and career trajectories of L&D professionals, the perceptions of multiple internal stakeholders of the effectiveness of L&D and the relationships between context, L&D roles, competencies/expertise, and perceived effectiveness. We gathered data using multiple methods: survey (n=440), Delphi study (n=125) and semi-structured interviews (n=30). The analysis revealed that L&D professionals increasingly respond to a multiplicity of external and internal contextual influences and internal stakeholders perceived the effectiveness of L&D professionals differently with significant gaps in perceptions of what L&D contributes to organisational effectiveness. L&D professionals perform both strategic and operational roles in organisations and they progress through four career levels. Each L&D role and career level requires a distinct and unique set of foundational competencies and L&D expertise. Finally, we found that different contextual predictors were important in explaining the perceived effectiveness of L&D roles and the importance attached to different foundational competencies and areas of L&D expertise. We discuss the implications for theory, research and practice

Scalable and accurate deep learning for electronic health records

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that discards the vast majority of information in each patient's record. We propose a representation of patients' entire, raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) format. We demonstrate that deep learning methods using this representation are capable of accurately predicting multiple medical events from multiple centers without site-specific data harmonization. We validated our approach using de-identified EHR data from two U.S. academic medical centers with 216,221 adult patients hospitalized for at least 24 hours. In the sequential format we propose, this volume of EHR data unrolled into a total of 46,864,534,945 data points, including clinical notes. Deep learning models achieved high accuracy for tasks such as predicting in-hospital mortality (AUROC across sites 0.93-0.94), 30-day unplanned readmission (AUROC 0.75-0.76), prolonged length of stay (AUROC 0.85-0.86), and all of a patient's final discharge diagnoses (frequency-weighted AUROC 0.90). These models outperformed state-of-the-art traditional predictive models in all cases. We also present a case-study of a neural-network attribution system, which illustrates how clinicians can gain some transparency into the predictions. We believe that this approach can be used to create accurate and scalable predictions for a variety of clinical scenarios, complete with explanations that directly highlight evidence in the patient's chart.Comment: Published version from https://www.nature.com/articles/s41746-018-0029-