Contributors

Abstract

The authors respond to an article on the role of the International Standard Serial Number (ISSN) as a manifestation (format) identifier of serials. They discuss some of the challenges that multiple manifestations present for the ISSN Network, some proposed solutions to this problem, and invite further input and dialogue on the topic. Serials Review 2003; 29:97–99.     

Employee financial wellness programs: Opportunities to promote financial inclusion?

ABSTRACT

Employee financial wellness programs (EFWPs) are a new practice that may promote financial inclusion by making it easier for workers with low- and moderate-incomes (LMI) to access financial services. We examine the strengths and limitations of workplace financial counseling, credit-building services, and small-dollar loans, and describe community collaboration to promote employee financial wellness. Findings suggest that these services are reaching a population that experiences financial exclusion, though evidence is mixed concerning how these services help workers with LMI resolve key financial challenges. Community collaboration focused on employee financial wellness presents opportunities to advocate for higher wages and better benefits.     

Truth® ads,receptivity, and motivation to use or quit tobacco among college students

Abstract

Objective: Examine receptivity and motivation to use/quit tobacco among college students after viewing Truth ads. Participants: Random sample of 10,000 college students invited to complete online survey February 2016 (8.5% response rate). Methods: Quasi-experimental. Participants (N?=?854) watched four ads and answered survey items for each ad. Results: Students rated ad receptivity and decreased motivation to use tobacco higher for the Catmageddon ad than the others. Regardless of ad, men and current cigarette smokers reported lower receptivity. Younger age was associated with lower motivation to use tobacco for all ads. Tobacco users reported greater motivation to quit with the Catmageddon ad. Conclusions: College students were receptive to the Truth ads, and many indicated lower motivation to use tobacco. Men, older college students, and current cigarette smokers were less receptive to the ads, reinforcing the need to develop tailored campaigns to reach these subgroups.     

Intergenerational Activities that Promote Engaging Conversations are Preferred among Young and Older Adults

ABSTRACT

Loneliness negatively affects young and older adults. Intergenerational activities foster social connectedness. Using quantitative and qualitative methods, this study explored which intergenerational activities are most enjoyable for college students and retirement community residents. Demographics, loneliness, enjoyment, conversation level, and type of activity were analyzed. The enjoyment and conversation variables were positively correlated (r = .59, p < .001) which was supported by participants’ narratives. Both populations most enjoyed the activities with higher conversation levels, with the first being committees, followed by meals, one on one activities, and transportation. Retirement communities and universities should promote intergenerational activities, which include meaningful conversations.     

Sticky Price Models of the Business Cycle: Can the Contract Multiplier Solve the Persistence Problem?

We construct a quantitative equilibrium model with firms setting prices in a staggered fashion and use it to ask whether monetary shocks can generate business cycle fluctuations. These fluctuations include persistent movements in output along with the other defining features of business cycles, like volatile investment and smooth consumption. We assume that prices are exogenously sticky for a short time. Persistent output fluctuations require endogenous price stickiness in the sense that firms choose not to change prices much when they can do so. We find that for a wide range of parameter values, the amount of endogenous stickiness is small. Thus, we find that in a standard quantitative model, staggered price‐setting, alone, does not generate business cycle fluctuations.     

Facing Faculty Fears about Embracing the Ebook: Communication Strategies for Liaison Librarians

Carol Cramer and Ellen Daugman of Wake Forest University discussed faculty attitudes toward ebooks in the library collection. Cramer and Daugman shared communication strategies based on their experience balancing the print book preferences of some faculty with the budgetary and collection development needs of the library.     

Development and Validation of a Multidimensional Measure of Family Supportive Supervisor Behaviors (FSSB)

Due to growing work-family demands, supervisors need to effectively exhibit family supportive supervisor behaviors (FSSB). Drawing on social support theory and using data from two samples of lower wage workers, the authors develop and validate a measure of FSSB, defined as behaviors exhibited by supervisors that are supportive of families. FSSB is conceptualized as a multidimensional superordinate construct with four subordinate dimensions: emotional support, instrumental support, role modeling behaviors, and creative work-family management. Results from multilevel confirmatory factor analyses and multilevel regression analyses provide evidence of construct, criterion-related, and incremental validity. The authors found FSSB to be significantly related to work-family conflict, work-family positive spillover, job satisfaction, and turnover intentions over and above measures of general supervisor support.     

The relative performance of ensemble methods with deep convolutional neural networks for image classification

Artificial neural networks have been successfully applied to a variety of machine learning tasks, including image recognition, semantic segmentation, and machine translation. However, few studies fully investigated ensembles of artificial neural networks. In this work, we investigated multiple widely used ensemble methods, including unweighted averaging, majority voting, the Bayes Optimal Classifier, and the (discrete) Super Learner, for image recognition tasks, with deep neural networks as candidate algorithms. We designed several experiments, with the candidate algorithms being the same network structure with different model checkpoints within a single training process, networks with same structure but trained multiple times stochastically, and networks with different structure. In addition, we further studied the overconfidence phenomenon of the neural networks, as well as its impact on the ensemble methods. Across all of our experiments, the Super Learner achieved best performance among all the ensemble methods in this study.