Curriculum renewal in translator training: vocational challenges in academic environments with reference to needs and situation analysis and skills transferability from the contemporary experience of Polish translator training culture

This work examines the principles underlying curriculum renewal for the training of translators. It considers recent work from Translation Studies on the nature of translation competence, arguing that a more dynamic understanding of the nature of translation must be reflected in a departure from traditional transmissionist pedagogical practices. Consideration of these issues in a curricular framework must also acknowledge the ideological potential of curricula themselves to prioritise certain relationships between the learner and society, relationships which are investigated from the perspective of a socially situated view of the translator. With regard to determining curricular orientation, a methodology of needs and situation analysis is suggested as a means of profiling essential characteristics of the translator’s work in specific contexts, informed by such issues as changing notions of translation, changing employment norms in the language services sector, locally prevailing norms in the educational environment, etc. Major issues impacting on the situational consideration of needs in translator training are examined, in particular the way in which the vocational / academic dichotomy may problematise training in academic environments. The notion of skills transferability is presented as a theme which is important both to the training of translators and to maximising social reconstructionist potentials in university curricula. In the final chapter, the issues presented in the first three chapters are discussed in relation to the challenges facing translator training in Polish universities with the implementation of Bologna Process reforms. In particular, Polish notions of academic and vocational education are analysed and the experience of one particular university philology is presented as a case study. The conclusion takes the themes discussed in the work and presents them in terms of the opposition between ‘training translators’ and ‘teaching translation.’ Future research trajectories are also proposed

The Igalirtuuq Conservation Initiative: An Exploration of Collaborative Multi-level Environmental Governance Formation

In 2010, the Ninginganiq National Wildlife Area (NNWA) was formally established at Isabella Bay, Baffin Island, Nunavut. This designation suggests the site’s importance for wildlife conservation, and as a potential component of an emerging network of Canadian marine protected areas. However, upon closer inspection, this wildlife area also represents a complex and lengthy initiative to conserve wildlife habitats, and to support local livelihoods and culture in the region. This long-term process, referred to here as the Igalirtuuq Conservation Initiative (ICI), dates back to the early 1980s when it began as a community driven initiative. Over the subsequent decades the initiative moved through several phases as it was shaped by surrounding socio-political events. The process remains ongoing today. This thesis takes an historical approach to understanding the formation of collaborative and multi-level environmental governance (CMEG). In order to do so, temporal and organizational, and thematic analyses are used to construct a detailed case study of the ICI. In addition to this, a framework of conditions for successful multi-level environmental governance is tested and refined based on the case study. This exploratory research finds that the many important conditions necessary for CMEG formation can be identified in governance theory, as well as by looking at social-political contexts specific to the case study

Defensive Medicine: Effect on Costs, Quality, and Access to Healthcare

Defensive medicine occurs when doctors deviate from sound medical practice in an attempt to minimize the possibility of malpractice liability. According to Studdert et al. (2005) the practice of defensive medicine affects healthcare in various ways by (a) supplementing care through additional testing or treatment, (b) replacing care when doctors refer patients to other doctors or institutions, and (c) reducing care by refusal to treat certain patients. Of primary concern is the growing evidence that defensive medicine is widely practiced and that it may increase the cost and lower the quality of care (Studdert et al.; Robeznieks, 2005). Any increased healthcare costs and lowered quality of healthcare as a result of defensive medicine could impact negatively on resource poor sub-saharan African countries already experiencing major healthcare issues.  The practice of defensive medicine has a negative impact on health care providers, patients, and the broader healthcare system. There is a need for medical malpractice reforms to reverse its adverse effects. Key words: Healthcare, malpractice, quality, costs, defensive medicine, healthcare access

A Finite-Horizon Approach to Active Level Set Estimation

We consider the problem of active learning in the context of spatial sampling for level set estimation (LSE), where the goal is to localize all regions where a function of interest lies above/below a given threshold as quickly as possible. We present a finite-horizon search procedure to perform LSE in one dimension while optimally balancing both the final estimation error and the distance traveled for a fixed number of samples. A tuning parameter is used to trade off between the estimation accuracy and distance traveled. We show that the resulting optimization problem can be solved in closed form and that the resulting policy generalizes existing approaches to this problem. We then show how this approach can be used to perform level set estimation in higher dimensions under the popular Gaussian process model. Empirical results on synthetic data indicate that as the cost of travel increases, our method's ability to treat distance nonmyopically allows it to significantly improve on the state of the art. On real air quality data, our approach achieves roughly one fifth the estimation error at less than half the cost of competing algorithms