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Presents the conclusions of Harris Interactive’s landmark poll of youth marketers, which reveals the industry’s views on complex issues like the ethics of selling to children, advertising in schools, violent content in the media, child nutrition and obesity. Outlines the method used, which consisted of 878 online interviews, classifying respondents into youth marketing, advertising and PR, media, non‐profit organisations, market research, and educational institutions. Identifies characteristics of each group over their views about children as consumers, ethics, role models, rating systems for movies and shows, and health. Concludes that those working in youth fields tend to defend their own organisation although they often criticise the industry as a whole.

Reports a study on by Harris Interactive on the reasons behind the millennium generation’s choices of media content, based on interviews with 2,518 American 13‐24 year olds and the use of correspondence analysis to develop a series of maps. Describes the segmentation model for millennials, dividing them into six groups with suggestions of how to reach them with brand messaging. Shows how millennials thrive in a fragmented media landscape that may overwhelm adults, and characterises each of the media on the map: internet, telephones, TV, magazines, radio, movies and newspapers. Emphasises the complexity of the internet: millennials want advertisers to erect signposts and on‐ramps on the information superhighway.

Parent satisfaction with their children's school is an important issue in today's competitive educational environment characterized by school choice and government standards; however, few empirical studies address school satisfaction similarities and differences among parents from different ethnic groups. The purpose of this paper is to determine empirically similarities as well as differences in the factors important to parents from different ethnic backgrounds.

This article presents a conceptual model of parent satisfaction with schools that was derived from the literature as well as researchers at the Harris Interactive Poll Organization. The article reports the findings from a survey of 27,605 African‐American, Asian, Caucasian, and Hispanic parents from 121 schools in 27 school districts across the US. Regression analyses identified factors that contribute to overall school satisfaction among the ethnic groups.

Ethnic parental groups share attributes with respect to school satisfaction; however, the importance groups place on such school characteristics as parental involvement, school administration, and technology varies. Across ethnic groups, parents' school satisfaction was influenced most by their rating of school safety, followed by the school budget and teacher effectiveness. Factors more proximal to children's school experience (e.g. safety, teachers, and facilities) had greater influence on parents' school satisfaction than factors of lesser proximity (e.g. district administration).

The study furthers our understanding of parent's school satisfaction with their children's schools, especially with respect to ethnicity. The study findings have practical implications for school administrators who must first understand parents' school satisfaction across and among ethnic groups, set priorities, and take action to increase parent school satisfaction.

Outlines the legislative structure surrounding advertising to children in Brazil, which is aimed at protecting children because of their lack of experience and vulnerability; it is based on the Brazilian Federal Constitution (BFC). Moves on to CONAR, the National Counsel [sic] of Advertising Self‐Regulation, which was set up by media associations in the 1980s and has a set of rules for ensuring that advertisers obey national regulations; and to the Brazilian Consumer Defence Code (CDC) enacted in 1990, which represents an increase in control by legislators and the judiciary. Indicates types of advertising prohibited: simulated, misleading and abusive, plus product placement. Concludes with provisions for participation of children in advertisements, and over the advertising of tobacco, alcoholic beverages, pesticides, medicine and guns.

The purpose of this paper is to describe how the authors gained a better understanding of the variety of library users' data needs, and how gradually some new data services were established based on current capabilities.

This paper uses a case study of the new data services at the John Cotton Dana Library, at Rutgers, The State University of New Jersey, Newark campus, to demonstrate the possible ways to extend data reference services and provide data computing services. A content analysis of services records shows how each user group falls into the multiple data services levels and subcategories.

Library users can be classified into many different categories, and each of these may have different needs. Research centers might have big projects involving data gathering and applications where a librarian can mainly provide consultation; while an individual faculty member or student might need the librarians as research partners, with help for their specific problems. Computing data services can involve group training and statistical analysis assistance, where researchers need emergent help. Data librarians can take various opportunities for data management education, thereby gradually raising awareness and cultivating better research habits among researchers.

Library data computing services can make unique contributions to faculty and students' research and study. Institution, library and users' interaction determines the levels and extent of data services and is generalized from the description and analysis of typical data service examples. Classic concept of data services levels is applied to a concrete case of data services program, and sub‐categories of each data services level and user types are developed based on the authors' services record.

This article is motivated by the lack of flexibility in Bayesian quantile regression for ordinal models where the error follows an asymmetric Laplace (AL) distribution. The inflexibility arises because the skewness of the distribution is completely specified when a quantile is chosen. To overcome this shortcoming, we derive the cumulative distribution function (and the moment-generating function) of the generalized asymmetric Laplace (GAL) distribution – a generalization of AL distribution that separates the skewness from the quantile parameter – and construct a working likelihood for the ordinal quantile model. The resulting framework is termed flexible Bayesian quantile regression for ordinal (FBQROR) models. However, its estimation is not straightforward. We address estimation issues and propose an efficient Markov chain Monte Carlo (MCMC) procedure based on Gibbs sampling and joint Metropolis–Hastings algorithm. The advantages of the proposed model are demonstrated in multiple simulation studies and implemented to analyze public opinion on homeownership as the best long-term investment in the United States following the Great Recession.