1,720,955 research outputs found
School Sense of Community, Teacher Support, and Students’ School Safety Perceptions
Full text linkThis study examined the association between two characteristics of school climate (sense of community and teacher support, measured both at the individual and at the school level) and students’ feelings of being unsafe at school. The study involved a sample of 49,638 students aged 10–18 years who participated in the 2010–2012 California Healthy Kids Survey. Using hierarchical linear modeling (HLM), our findings revealed that, at the individual level, students perceiving higher levels of sense of community and teacher support at school were less likely to feel unsafe within the school environment. At the school level, sense of community was negatively associated with unsafe feelings, whereas there was no association between school-level teacher support and feelings of being unsafe at school
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Straight from the Source: Using Client Strengths and Risks to Predict Future Supervision Violations
Full text linkThe number of individuals convicted of crime in the United States is large, and re-conviction rates among these individuals is even higher. Criminal conviction and recidivism rates are concerning for a variety of reasons, most of which are related to the various deleterious outcomes found to be associated with criminal justice involvement. The extant literature on factors related to recidivism focus primarily on unalterable risk factors and alterable risk factors; however, there is still a dearth of research on which alterable strength factors are associated with recidivism, and how patterns of risks and strengths relate to recidivism. The present research addresses some of these gaps by investigating: (a) if established strengths-based internal assets scales are internally reliable for use with criminal justice-involved populations; (b) if classes of clients can be ascertained on a number of alterable strengths (i.e., twelve-step support, self-efficacy, cognitive reappraisal), alterable risks (i.e., difficulty with: transportation, housing, employment, substance use), and an unalterable risk measure (i.e., a standardized risk assessment score derived from prior convictions and personal history; Recidivism Risk from the COMPAS); (c) if ethnicity functions as a significant covariate between emerging classes; and (d) if the emerging classes significantly predict recidivism (i.e., supervision violations) within three-months post-completion of the initial survey. The initial sample for the reliability analyses consisted of N = 333 clients serving time under community supervision at a probation agency in California, due to primarily substance-related convictions. Clients were all identified as male, 58% were identified as Hispanic and 42% White, M = 39 years old. After variables were selected for use in the LCA and observations with missing data were eliminated, the final sample utilized in the LCA was N = 262. The internal reliability analyses revealed very high internal reliability statistics (α = .91 to .95) on the internal asset scales examined (self-efficacy, self-awareness, cognitive reappraisal, self-regulation). This is an important contribution due to the limited number of studies that examine strengths-based and internal asset scales with criminal justice-involved populations; future research would benefit from continuing to explore these measures and their utility with this population. Next, the LCA analyses revealed strong fit indices for a three-class model that was delineated as representing: Low Strengths, High Risks (45%); High Strengths, Low Risks (29%), and Very Low Strengths, Low Risks (26%). Of note was that the unalterable risk factor (i.e., Recidivism Risk) was not a notable factor in distinguishing class membership. In the covariate analysis, class membership was not found to be divergent by ethnicity. When recidivism (i.e., acquisition of supervision violations within three months of post-completion of the survey) was added as a distal outcome to the three-class solution, significant differences between the three classes emerged on the probability of whether or not an individual was likely to acquire supervision violations. Specifically, the Low Strengths, High Risks population was significantly more likely to acquire supervision violations than the other two classes of clients (High Strengths, Low Risks; Very Low Strengths, Low Risks). The research suggests that clients may be able to be screened by use of alterable risk and alterable strengths in preventing or identifying propensity toward recidivism. Based on the lack of discriminant ability of the unalterable risk factor (based largely on criminal history), it is unclear now what the utility of an unalterable measure may be in such a screening tool. The use of LCA in this study provides an innovative way to bridge research into practice, in that practitioners and individuals in direct contact with similar criminal justice-involved clients could utilize results of these analyses to develop client profiles to intervene or provide additional supports to clients, in an effort to prevent recidivism. This research has important implications due to the various gaps in the literature; the potential for this research to be immediately useful and applicable for practitioners, policymakers, and researchers; and the general lack of strengths-based approaches used with criminal-justice involved populations that may help to better understand factors related to recidivism, and thus help deter the various negative outcomes that are associated with continued criminal justice involvement
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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