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21 – 30 of 88Sue Starfield, Brian Paltridge and Louise Ravelli
This chapter discusses textography as a strategy for researching academic writing in higher education. Textography is an approach to the analysis of written texts which combines…
Abstract
This chapter discusses textography as a strategy for researching academic writing in higher education. Textography is an approach to the analysis of written texts which combines text analysis with ethnographic techniques, such as surveys, interviews and other data sources, in order to examine what texts are like, and why. It aims to provide a more contextualized basis for understanding students’ writing in the social, cultural and institutional settings in which it takes place than might be obtained by looking solely at students’ texts. Through discussion of the outcomes of a textography, which examined the written texts submitted by visual and performing arts doctoral students at a number of Australian universities, we reflect on what we learnt from the study that we could not have known by looking at the texts alone. If we had looked at the texts without the ethnographic data not only are there many things we would not have known, but many of the things we might have said would likely have been right off the mark. Equally, had we just had the ethnographic data without the text analysis, we would have missed the insights provided by the explicit text analysis. The textography enabled us to see the diversity of practices across fields of study and institutions as well as gain an understanding of why this might be the case, all of which is of benefit to student writers and their supervisors.
Katherine M. Johnson, Richard M. Simon, Jessica L. Liddell and Sarah Kington
There has been substantial interest in US cesarean rates, which increased from 5% of deliveries in the 1970s to nearly one-third of births by the mid-2000s. Explanations typically…
Abstract
There has been substantial interest in US cesarean rates, which increased from 5% of deliveries in the 1970s to nearly one-third of births by the mid-2000s. Explanations typically emphasize individual risk factors (e.g., advanced maternal age, increased BMI, and greater desire for control over delivery) of women giving birth, or address institutional factors, such as the medicalization of childbirth and the culture of liability leading physicians to practice defensive medicine. We focus here on another non-medical explanation – childbirth education (CBE). CBE is an important, underexplored mechanism that can shape women’s expectations about labor and birth and potentially lead them to expect, or desire, a cesarean delivery as a normalized outcome. We analyze data from three waves (2002, 2006, 2013) of the Listening to Mothers national survey on US women’s childbearing experiences (n = 3,985). Using logistic regression analysis, we examined both mode of delivery (vaginal versus cesarean), and attitudes about future request for elective cesarean among both primiparous and multiparous women. Despite previous research suggesting that CBE increased the likelihood of vaginal delivery, we find that CBE attendance was not associated with likelihood of vaginal delivery among either primiparous or multiparous women. However, both primiparous and multiparous women who attended CBE classes were significantly more likely to say they would request a future, elective cesarean. Furthermore, these effects were in the opposite direction of effects for natural birth attitudes. Our findings suggest that contemporary CBE classes may be a form of “anticipatory socialization”, potentially priming women’s acceptance of medicalized childbirth.
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Just as the films that we see are conceived in specific economic, political and cultural contexts, so scholarship is produced within determined situations. This chapter notes some…
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Just as the films that we see are conceived in specific economic, political and cultural contexts, so scholarship is produced within determined situations. This chapter notes some of the driving forces which have led to the emergence of law and film as an area of extensive and very diverse scholarship in the past decade. Whilst these factors have shaped the nature and extent of this work it should be noted that changes in both legal professional interests, academic criteria and within the culture industry mean that we can expect shifts in the nature and patterns of scholarship in the future. These may not, however, be the ones called for by other commentators (Moran, Sandon, Loizidou, & Christie, 2004; Sarat, Douglas, & Umphrey, 2005).
Jaron Harvey, Mark C. Bolino and Thomas K. Kelemen
For decades organizational citizenship behavior (OCB) has been of interest to scholars and practitioners alike, generating a significant amount of research exploring the concept…
Abstract
For decades organizational citizenship behavior (OCB) has been of interest to scholars and practitioners alike, generating a significant amount of research exploring the concept of what citizenship behavior is, and its antecedents, correlates, and consequences. While these behaviors have been and will continue to be valuable, there are changes in the workplace that have the potential to alter what types of OCBs will remain important for organizations in the future, as well as what types of opportunities for OCB exist for employees. In this chapter we consider the influence of 10 workplace trends related to human resource management that have the potential to influence both what types of citizenship behaviors employees engage in and how often they may engage in them. We build on these 10 trends that others have identified as having the potential to shape the workplace of the future, which include labor shortages, globalization, immigration, knowledge-based workers, increase use of technology, gig work, diversity, changing work values, the skills gap, and employer brands. Based on these 10 trends, we develop propositions about how each trend may impact OCB. We consider not only how these trends will influence the types of citizenship and opportunities for citizenship that employees can engage in, but also how they may shape the experiences of others related to OCB, including organizations and managers.
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Darrin Kass and Christian Grandzol
This study examined the leadership development of MBA students enrolled in an Organizational Behavior course. Students enrolled in either an in-class section or a section that…
Abstract
This study examined the leadership development of MBA students enrolled in an Organizational Behavior course. Students enrolled in either an in-class section or a section that included an intensive, outdoor training component called Leadership on the Edge. Results from Kouzes and Posner’s Leadership Practices Inventory (2003) showed that students in the outdoor training section demonstrated greater improvements in leadership practices over the course of the semester. Reflective comments from students in the outdoor section indicated it was a transformative personal experience that is unlikely to be emulated in a classroom. Implications for leadership educators are discussed.
Most scholarly and governmental discussions about artificial intelligence (AI) today focus on a country’s technological competitiveness and try to identify how this supposedly new…
Abstract
Most scholarly and governmental discussions about artificial intelligence (AI) today focus on a country’s technological competitiveness and try to identify how this supposedly new technological capability will improve productivity. Some discussions look at AI ethics. But AI is more than a technological advancement. It is a social question and requires philosophical inquiry. The producers of AI who are software engineers and designers, and software users who are human resource professionals and managers, unconsciously as well as consciously project direct forms of intelligence onto machines themselves, without considering in any depth the practical implications of this when weighed against human actual or perceived intelligences. Neither do they think about the relations of production that are required for the development and production of AI and its capabilities, where data-producing human workers are expected not only to accept the intelligences of machines, now called ‘smart machines’, but also to endure particularly difficult working conditions for bodies and minds in the process of creating and expanding the datasets that are required for the development of AI itself. This chapter asks, who is the smart worker today and how does she contribute to AI through her quantified, but embodied labour?
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