Influential Social Workers: A Preliminary Exploration of Social Work Faculty

The profession of social work in the U.S. has been influenced and is being influenced by a wide-range of advocates, politicians, practitioners, and educators. This paper is a preliminary attempt to systematically examine who social work faculty consider influential in shaping the field. Identifying influential social workers is an important step in understanding the history of a profession, its current state, and its future trajectory.

Low rank subspace clustering (LRSC)

We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.

The Critical Friends Group: An Innovative Way to Build Intercultural Competence Among Student and Faculty Groups

Introduction Few physicians involved in medical education are likely to have had formal training in teaching. One pedagogical method that can enhance relationships, thus improve teaching and learning is the Critical Friends Group (CFG). The CFG is a collegial support team that offers improved understanding of others. Unconditional high regard for team members frames the interactions in the CFG. These teams could be used to reduce bias and enhance intercultural competence among student CFGs and faculty CFGs. [See PDF for complete abstract]

Citation analysis of faculty publication: beyond Science Citation Index and Social Science Citation Index.

When evaluated for promotion or tenure, faculty members are increasingly judged more on the quality than on the quantity of their scholarly publications. As a result, they want help from librarians in locating all citations to their published works for documentation in their curriculum vitae. Citation analysis using Science Citation Index and Social Science Citation Index provides a logical starting point in measuring quality, but the limitations of these sources leave a void in coverage of citations to an author's work. This article discusses alternative and additional methods of locating citations to published works.

The Place of the Hoplocarida in the Malacostracan Pantheon

The stomatopod body plan is highly specialized for predation, yet the Superorder Hoplocarida originated from something other than the "lean, mean, killing machine" seen today. The fossil record of the group indicates that it originated early on from a non-raptorial ancestor, with the specialized predatory morphology developing much later. The Recent Hoplocarida have been variously positioned within the Malacostraca, from a Subclass equal in rank to the Eumalacostraca (= Caridoida) to being placed as a Superorder within the Eumalacostraca. Consideration of the early fossil morphology, especially of the form of the carapace, of the position and functioning of the articles in the last three pairs of thoracopods, and of other features, suggests that hoplocarids are early derivatives of a basal eumalacostracan stock that was "shrimp-like" in form. The enhancement of an abdominal respiratory system most likely allowed the development of the anterior thorax into the specialized raptorial system present today.

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Increasingly Rank: The Use and Misuse of Rankings in Economic Development

Debates over the merits of competing schemes for ranking metropolitan areas as hightech centers shed little light on the important policy questions that should be the core of economic development policy. There are no strong theoretical reasons for preferring one ranking system to others. Rankings often conflate different industries and ignore history, obscuring the varied and often idiosyncratic processes that drive growth in different regions. Although an occupational perspective is a useful one for examining economic activity, it is a supplement to, not a replacement for, a careful understanding of metropolitan industrial specialization. Practitioners should not put too much weight on any ranking system but instead should work to develop detailed knowledge of their region’s special economic niche and to develop relationships and strategies that build on established strengths.

Application of Local Rank Tests for Nonparametric Regression

Let Y_i = f(x_i) + E_i\ (1\le i\le n) with given covariates x_1\lt x_2\lt \cdots\lt x_n , an unknown regression function f and independent random errors E_i with median zero. It is shown how to apply several linear rank test statistics simultaneously in order to test monotonicity of f in various regions and to identify its local extrema.

Environmental correlates of species rank − abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

Community College Student Participation in Undergraduate Research: An Explanatory Case Study for Faculty and Research Mentors

This study adapted the current model of science undergraduate research experiences (URE's) and applied this novel modification to include community college students. Numerous researchers have examined the efficacy of URE's in improving undergraduate retention and graduation rates, as well as matriculation rates for graduate programs. However, none have detailed the experience for community college students, and few have employed qualitative methodologies to gather relevant descriptive data from URE participants. This study included perspectives elicited from both non-traditional student participants and the established laboratory community. The purpose of this study was to determine the effectiveness of the traditional model for a non-traditional student population. The research effort described here utilized a qualitative design and an explanatory case study methodology. Six non-traditional students from the Maine Community College System participated in this study. Student participants were placed in six academic research laboratories located throughout the state. Student participants were interviewed three times during their ten-week internship and asked to record their personal reflections in electronic format. Participants from the established research community were also interviewed. These included both faculty mentors and other student laboratory personnel. Ongoing comparative analysis of the textual data revealed that laboratory organizational structure and social climate significantly influence acculturation outcomes for non-traditional URE participants. Student participants experienced a range of acculturation outcomes from full integration to marginalization. URE acculturation outcomes influenced development of non-traditional students? professional and academic self-concepts. Positive changes in students? self-concepts resulted in greater commitment to individual professional goals and academic aspirations. The findings from this study suggest that traditional science URE models can be successfully adapted to meet the unique needs of a non-traditional student population – community college students. These interpretations may encourage post-secondary educators, administrators, and policy makers to consider expanded access and support for non-traditional students seeking science URE opportunities.

Comparing Psychological Type and Explanatory Between Nursing Students and Clinical Faculty: A Pilot Study

Negotiation of complex collaboration and effective teamwork among health care providers is essential to patient safety and to quality of care. This study examined characteristics of nursing students and faculty influencing communication between them. Psychological type (Myers-Briggs Type Inventory (MBTI) (Myers, McCaulley, Quenk, & Hammer, 1998) and explanatory style (Attributional Style Questionnaire) (ASQ) (Peterson et al., 1982) were compared for participating first year baccalaureate nursing students (N=286), and clinical nursing faculty (N=59) from both two- and four-year nursing programs. Modal student psychological type was ESFJ; modal faculty psychological type was ISTJ. The two groups demonstrated significant differences in processing information, and making decisions and judgments. Students were slightly more optimistic than faculty. Psychological type and level of optimism did not appear to correlate. Data from this pilot study provide an initial framework on which to base further research that could enhance the quality of teamwork among healthcare providers.