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Featured submissions

February 2019

January 2019 

  • Disrupting Traditional Power Structures in Academic Libraries: Saying No, How to Do it, and Why it Matters

    Cassidy, Melanie; Versluis, Ali; Menzies, Erin; University of Guelph; University of Guelph; Ontario Ministry of Health and Long-Term Care (The University of Arizona, 2018-11-16)
    Many academic libraries face austerity measures, personnel reductions, or compression; the weight of increased workloads results in diminished mental health, increased precarity, and an inability to engage in critical teaching and learning practices. These challenges sit at the intersection of resilience, precarity, and neoliberalism. Within academic libraries, resilience is endorsed as a means of negotiating precarious employment by encouraging non-permanent staff to continually prove their value to the institution or risk not being retained. The neoliberal perspective endorses an environment where individual culpability is assigned at the cost of challenging institutional practices. This session seeks to interrogate our position as library staff within this construct, both in terms of how we are influenced by this intersection and how we support it. Participants will share experiences, develop best practices, and establish a “resilience taxonomy” to provide support in resisting overwork, precarity, and other negative side-effects of the neoliberal academic library.
  • It Is Time to Cancel Medicine’s Social Contract Metaphor

    Harris, John M.; Univ Arizona, Coll Med, Continuing Med Educ (LIPPINCOTT WILLIAMS & WILKINS, 2017-09)
    There is agreement that the complex relationship between medicine and society is best described as a metaphorical social contract and that professionalism is the medical profession's contribution to this contract. Metaphors can help clarify abstract concepts, but they can also be abused if the counterfactual attributes of a metaphor become attributed to its subject. This seems to be happening with medical professionalism, which has sometimes been reduced to a contracted deliverable and a bargaining chip. The undesirable attributes of the social contract metaphor may be hindering efforts to understand and teach medical professionalism. Despite its theoretical weaknesses, the social contract metaphor has historical credibility because of its alleged association with the 1847 Code of Medical Ethics and the subsequent ascension of regular (allopathic) medicine in the early 20th century. However, the record does not support an argument that the intended purpose of the 1847 Code was to create a social contract or that one ever arose. The alternative account that a contract did arise, but physicians were poor partners, is neither satisfying nor explanatory. As now used, medicine's social contract metaphor has serious theoretical and historic weaknesses. Medical educators should remove this narrow and overworked metaphor from their discussions of professionalism. By doing this, educators and the profession in general would only lose the ability to threaten themselves with the cancellation of their social contract. In return they would open the door to a more complex and fruitful consideration of medical professionalism and medicine's relationship with society.
  • A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

    Babazadeh, Reza; Ghaderi, Hamid; Pishvaee, Mir Saman; Univ Arizona, Dept Syst & Ind Engn (PERGAMON-ELSEVIER SCIENCE LTD, 2019-05-08)
    This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total cost of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran. (C) 2019 Elsevier Ltd. All rights reserved.
  • Exit Tales: How Precarious Workers Navigate Bad Jobs

    Sallaz, Jeffrey J.; Univ Arizona, Sch Sociol (SAGE PUBLICATIONS INC, 2017-10)
    Why do some workers quit undignified bad jobs, while others persist in them? We know a great deal about how people find employment, along with what they do at work. But we have few studies documenting the lived experience of quitting a bad job. Recent structural transformations, such as the demise of Fordism and the curtailment of welfare, have surely recalibrated the strategies by which precarious individuals navigate the labor market. This article, an ethnography that follows a single cohort of call center employees over nine months, documents four main pathways through which such workers leave versus stay in their jobs. It argues that the emergent class of precarious workers is not homogenous. Gender, race, and age intersect with class to shape how one experiences a given bad job.
  • Escape from Third-Best: Rating Emissions for Intensity Standards

    Lemoine, Derek; Univ Arizona, Dept Econ, Eller Coll Management (SPRINGER, 2017-08)
    An increasingly common type of environmental policy instrument regulates the carbon intensity of transportation and electricity markets. In order to extend the policy's scope beyond point-of-use emissions, regulators assign each potential fuel an emission intensity rating for use in calculating compliance. I show that welfare-maximizing ratings do not generally coincide with the best estimates of actual emissions. In fact, the regulator can achieve a higher level of welfare by properly selecting the emission ratings than possible by selecting only the level of the standard. Moreover, a fuel's optimal rating can actually decrease when its estimated emission intensity increases. Numerical simulations of the California Low-Carbon Fuel Standard suggest that when recent scientific information increased the estimated emissions from conventional ethanol, regulators should have lowered ethanol's rating (making it appear less emission-intensive) so that the fuel market would clear with a lower quantity.

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