排序方式： 共有6条查询结果，搜索用时 187 毫秒
1
1.
Loni Crumb Angie D. Cartwright Dominique S. Hammonds Janeé Avent Harris 《Counselor Education & Supervision》2023,62(3):233-247
The perceptions of personal and professional identity development from four Black women counselor educators were examined through a collaborative autoethnography methodology. Themes identified include (a) intentionality of code-switching, (b) inextricable identities, (c) fight for and with authenticity, and (d) mutual development of personal and professional identities. 相似文献
2.
Natoya H. Haskins Jolie Ziomek‐Daigle Cheryl Sewell Lonika Crumb Brandee Appling Heather Trepal 《Counselor Education & Supervision》2016,55(1):60-75
Using phenomenological inquiry, this study explored the lived experiences and intersecting identities of 8 African American counselor educators who are mothers. Six themes were identified: race, professional strain, work–life balance, support, internalized success, and mothering pedagogy. 相似文献
3.
Content analysis of e-petitions with topic modeling: How to train and evaluate LDA models? 总被引：1，自引：0，他引：1
Loni Hagen 《Information processing & management》2018,54(6):1292-1307
E-petitions have become a popular vehicle for political activism, but studying them has been difficult because efficient methods for analyzing their content are currently lacking. Researchers have used topic modeling for content analysis, but current practices carry some serious limitations. While modeling may be more efficient than manually reading each petition, it generally relies on unsupervised machine learning and so requires a dependable training and validation process. And so this paper describes a framework to train and validate Latent Dirichlet Allocation (LDA), the simplest and most popular topic modeling algorithm, using e-petition data. With rigorous training and evaluation, 87% of LDA-generated topics made sense to human judges. Topics also aligned well with results from an independent content analysis by the Pew Research Center, and were strongly associated with corresponding social events. Computer-assisted content analysts can benefit from our guidelines to supervise every process of training and evaluation of LDA. Software developers can benefit from learning the demands of social scientists when using LDA for content analysis. These findings have significant implications for developing LDA tools and assuring validity and interpretability of LDA content analysis. In addition, LDA topics can have some advantages over subjects extracted by manual content analysis by reflecting multiple themes expressed in texts, by extracting new themes that are not highlighted by human coders, and by being less prone to human bias. 相似文献
4.
Loni Crumb Rufus Larkin Ca Trice Glenn Jennifer Smith Ann Howard Marquita Johnson 《Community College Journal of Research & Practice》2013,37(7):455-458
ABSTRACTSexual misconduct is a major psychological, emotional, and public health crisis that manifests itself in social and academic arenas including community college campuses. Problems of sexual misconduct that emerge for women and men are not based solely on a difference in gender, but in silence once an incident occurs. The strife that emerges for students can be devastating and pervasive. College counselors, who provide counseling services and training programs, can offset the potentially negative consequences. This article highlights a training program for student leaders that underscores the significance of reporting sexual misconduct incidents at a 2-year college. This article provides percentage data to reflect the perceptions participants had following such training. The training discussed will further the understanding of how to take a proactive approach in reporting incidents of sexual misconduct. Prompting research along this line of training will provide important information to college-student personnel who are vested in creating a transformation to decrease incidents of sexual misconduct on 2-year college campuses. 相似文献
5.
Loni Hagen Thomas E. Keller Xiaoyi Yerden Luis Felipe Luna-Reyes 《Government Information Quarterly》2019,36(4):101387
Government agencies collect large amounts of structured and unstructured data. Although these data can be used to improve services as well as policy processes, it is not always clear how to analyze the data and how to glean insights for policy making, especially when the data includes large volumes of unstructured text data. This article reports opinions found in “We the People” petition data using topic modeling and visual analytics. It provides an assessment of the usability of the visual analytics results for policy making based on interviews with data professionals and policy makers. We found that visual analytics have potentially positive impacts on policy making practices. Experts also articulated potential barriers regarding the adoption of visual analytics tools, and made suggestions. Potential barriers included insufficient resources in government agencies and difficulty integrating analytics with current work practices. The main suggestions involved providing training and interpretation guidelines along with the visual analytics tools. Major contributions of this study include: (1) suggesting viable visualization tools for analyzing textual data for policy making, and (2) suggesting how to lower barriers to adoption by increasing usability. 相似文献
6.
Crowe Allison Averett Paige Harris Janee &#; R. Avent Crumb Loni Dietz Syntia Santos 《International journal for the advancement of counseling》2022,44(3):453-468
International Journal for the Advancement of Counselling - Globally, mental illness is still stigmatized by many. The following qualitative study explored beliefs about mental illness and help... 相似文献
1