Labour Market Under-Utilisation of Recent Higher Education Graduates: New Australian Panel Evidence

Recent research into the Australian labour market has reported that a substantial proportion of the tertiary-educated labour force is under-utilised relative to their level of education, echoing findings from an expanding international literature. This paper uses recent panel data from the 2010 Beyond Graduation Survey to analyse the incidence of labour force under-utilisation amongst recent Australian graduates and its effect on their wages, with an under-utilised graduate defined as a one who is in a job for which a sub-degree qualification would suffice. We find that 26% of graduates were under-utilised immediately after course completion and 15% were under-utilised three years later, although this varied considerably between subgroups. Recent graduates were much more likely to remain under-utilised than become under-utilised later in their careers. Being under-utilised appears to affect the earnings of different graduate age groups in different ways. Controlling for unobserved heterogeneity, we find that younger graduates tend to earn the same mean wages regardless of whether or not they are under-utilised, while older under-utilised bachelor degree graduates are at a significant wage disadvantage relative to their peers. This is suggestive of a graduate skills surplus and, by extension, inefficient public and individual investment in human capital.graduate labour market, human capital, panel data

Strategies to improve retention of postgraduate business students in distance education courses: an Australian case

In spite of the clear value of postgraduate business students to many providers of distance education courses, the factors affecting the retention of these students have received limited attention in the literature. In addressing this gap, this paper presents the findings of a qualitative study into the factors affecting the retention of postgraduate business students at a major Australian distance education university. The findings of this study suggest that a range of situational, dispositional and attitudinal factors impact upon student retention on this context, both as enablers of and obstacles to ongoing participation. In many cases, these factors differ to those identified in the existing literature on student retention. Based on these findings, we present a range of strategies designed to improve the retention of postgraduate business students by maximising enabling factors and minimising the impact of any identified obstacles. Limitations of the study and suggestions for further research are also presented

Learning to predict distributions of words across domains

Although the distributional hypothesis has been applied successfully in many natural language processing tasks, systems using distributional information have been limited to a single domain because the distribution of a word can vary between domains as the word’s predominant meaning changes. However, if it were possible to predict how the distribution of a word changes from one domain to another, the predictions could be used to adapt a system trained in one domain to work in another. We propose an unsupervised method to predict the distribution of a word in one domain, given its distribution in another domain. We evaluate our method on two tasks: cross-domain part-of-speech tagging and cross-domain sentiment classification. In both tasks, our method significantly outperforms competitive baselines and returns results that are statistically comparable to current state-of-the-art methods, while requiring no task-specific customisations

Quintessential Difficulties

An alternative to a cosmological constant is quintessence, defined as a slowly-varying scalar field potential V(\phi). If quintessence is observationally significant, an epoch of inflation is beginning at the present epoch, with \phi the slowly-rolling inflaton field. In contrast with ordinary inflation, quintessence seems to require extreme fine tuning of the potential V(\phi). The degree of fine-tuning is quantified in various cases.Comment: 7 pages LaTeX. Revised to be more pedagogical; results unchange

The Cube Recurrence

We construct a combinatorial model that is described by the cube recurrence, a nonlinear recurrence relation introduced by Propp, which generates families of Laurent polynomials indexed by points in $\mathbb{Z}^3$. In the process, we prove several conjectures of Propp and of Fomin and Zelevinsky, and we obtain a combinatorial interpretation for the terms of Gale-Robinson sequences. We also indicate how the model might be used to obtain some interesting results about perfect matchings of certain bipartite planar graphs

Evaluation of LTAG parsing with supertag compaction

One of the biggest concerns that has been raised over the feasibility of using large-scale LTAGs in NLP is the amount of redundancy within a grammar¿s elementary tree set. This has led to various proposals on how best to represent grammars in a way that makes them compact and easily maintained (Vijay-Shanker and Schabes, 1992; Becker, 1993; Becker, 1994; Evans, Gazdar and Weir, 1995; Candito, 1996). Unfortunately, while this work can help to make the storage of grammars more efficient, it does nothing to prevent the problem reappearing when the grammar is processed by a parser and the complete set of trees is reproduced. In this paper we are concerned with an approach that addresses this problem of computational redundancy in the trees, and evaluate its effectiveness

Cross-domain sentiment classification using a sentiment sensitive thesaurus

Automatic classification of sentiment is important for numerous applications such as opinion mining, opinion summarization, contextual advertising, and market analysis. However, sentiment is expressed differently in different domains, and annotating corpora for every possible domain of interest is costly. Applying a sentiment classifier trained using labeled data for a particular domain to classify sentiment of user reviews on a different domain often results in poor performance. We propose a method to overcome this problem in cross-domain sentiment classification. First, we create a sentiment sensitive distributional thesaurus using labeled data for the source domains and unlabeled data for both source and target domains. Sentiment sensitivity is achieved in the thesaurus by incorporating document level sentiment labels in the context vectors used as the basis for measuring the distributional similarity between words. Next, we use the created thesaurus to expand feature vectors during train and test times in a binary classifier. The proposed method significantly outperforms numerous baselines and returns results that are comparable with previously proposed cross-domain sentiment classification methods. We conduct an extensive empirical analysis of the proposed method on single and multi-source domain adaptation, unsupervised and supervised domain adaptation, and numerous similarity measures for creating the sentiment sensitive thesaurus

Saving and Growth: A Reinterpretation

We examine the relationship between income growth and saving using both cross-country and household data. At the aggregate level, we find that growth Granger causes saving, but that saving does not Granger cause growth. Using household data, we find that households with predictably higher income growth save more than households with predictably low growth. We argue that standard Permanent Income models of consumption cannot explain these findings, but that a model of consumption with habit formation may. The positive effect of growth on saving implies that previous estimates of the effect of saving on growth may be overstated.

Developing Dispositions for Ambitious Teaching

Critics of teacher education in recent years have argued that attempts to assess dispositions for teaching amount to a process of political indoctrination, claiming that teacher candidates are often expected to endorse ideas like “white privilege” and “social justice” as a kind of political litmus test for entering the teaching profession. In some circumstances, teacher education programs have avoided this kind of controversy by limiting their attention to dispositions such as honesty, integrity, and professional interactions. Charges and counter charges about the potential political implications of dispositions, and lack of clarity about other dimensions of dispositions, have obscured fundamental associations between personal beliefs and professional ethics, and between dispositions and ambitious conceptions of teaching. At the same time, little attention has been devoted to gaining a deeper understanding of dispositions for teaching, how they play a role in learning to teach, and how teacher education programs can support teacher candidates in developing dispositions for the kinds of challenging and complex teaching needed to do well by all children. This essay examines these issues and proposes ways in which teacher education can both support and assess the development of dispositions among teacher candidates