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PurposeSocially responsible organizations strive to foster gender diversity values in the workplace. As women, relative to men, tend to fall victim to gender discrimination more frequently, organizations can promote gender diversity in the workplace by either increasing female employment or discouraging job seekers who resist gender diversity from applying for positions. While more attention has been devoted to the former approach, less attention has been given to the latter.Design/methodology/approachA between-subjects experiment is conducted to test the hypotheses. Participants are randomly assigned to one of five conditions that feature different numbers of women in job advertisements.FindingsFor male job seekers who hold a male breadwinner ideology, their job pursuit intentions decrease as the number of women in job advertisements increases. Perceived person-organization fit acts as the mediating influence.Practical implicationsJob advertisements are purposed to attract job seekers who share similar values. Men who embrace male-dominant values are likely to resist and thwart the progress of gender diversity in the workplace. This study informs practitioners of how by strategically adapting job advertisements, organizations can discourage individuals who are likely to be a poor fit from applying for vacant jobs.Originality/valueThis study focuses on gender discrimination and resistance in a job seeking context from a social dominance perspective. The study informs organizations of the potential benefits of strategically adapting job advertisements.

This article examines the role of internet-based labour market intermediaries in coordinating job seeker/employer interactions. A twofold analysis examines on the one hand the matchmaking tools determining applicants' access to job ads, and on the other, the content of ads posted on the Web. Observations reveal that the information available to applicants is subject to a high degree of filtering achieved through the use of pre-defined lists, keywords or more frequently, input fields. A comparative analysis of job offers posted on the internet with those posted in newspapers shows that search engine toolkits have a considerable impact on ad content which is generally more standardized and quantified in the former than in the latter. Furthermore, a comparison between French and British ads demonstrates that the institutional context influences the actions taken by job boards. In contrast to Great Britain, France more frequently uses matching markers aimed at selecting applicants than those providing detailed information on the job offer. Today, French job boards thus contribute in weakening applicants' position in labour markets.

Given the lack of research into native-speakerism among teachers of languages other than English (LOTEs), this qualitative study aims to bridge the gap by investigating the discriminatory and inclusive language employed in online recruitment for post-secondary institution instructors of LOTEs. The study also looks at how post-secondary institutions phrase language requirements and whether there is a difference in "native-speaker-teacher" bias depending on the language. For the purposes of this study, qualitative content analysis was used to examine 187 online job advertisements for teaching positions of different LOTEs that were posted by different post-secondary institutions across the United States. The findings of the study show that post-secondary institutions use discriminatory language such as "native" or "near-native" much more often than inclusive language such as "superior language skills," regardless of the language(s) that the position advertises for. The findings, however, show that job candidates for teaching positions of LOTEs are often required to have "native" or "near-native" proficiency in at least two languages, most commonly English plus the target language of focus.

Introduction: For some years practitioners have observed a tendency that local government authorities advertising vacant professional positions in public libraries do not specify an educational background from library and information science as a mandatory qualification for applicants. Are the observers correct? This study aims at answering this question by analysing advertisements for vacant positions. Method: All advertised vacant positions registered at the Norwegian Labour and Welfare organisation in the years 2005, 2010 and 2015 satisfying a definition of having a professional responsibility were coded and analysed in order to see if the demand for professional education has changed over time. Analysis: A consecutive cross-sectional study was undertaken using quantitative content analysis. Results: The research confirmed that a development has taken place with a reduced weight on library education and an increased weight on personal and interpersonal traits between 2005 and 2015. There are differences between local government authorities according to size. The tendency not to ask for library education is strongest with the very small authorities and a few very large cities. Conclusions: Further research with longer time series as well as comparative research is needed to get a fuller understanding of the development. ; publishedVersion

In the tourism sector, employees are an essential element in the continuation of their activities and in providing quality service to their customers. With the industry becoming more competitive, every business wants to have qualified employees. This desire leads to an increase in the qualifications that companies are looking for in their employees. In this context, the primary purpose of this research is to determine the qualifications sought by the employees by examining the job advertisements of enterprises in the tourism sector. The study's data were obtained on the relevant website on September 23, 2022. On this date, there are 260 advertisements published within the last 15 days. Two hundred sixty job advertisements were analyzed by content analysis. Qualifications written in job advertisements were evaluated according to themes and codes with the Maxqda program. Five main themes were determined as employee personality traits, working conditions, management skills, program usage and other. The most desired employee qualities by businesses are the development of communication skills in employee personality traits, to be in harmony with the principle of teamwork and guest satisfaction in working conditions, having a problem-solving ability of employees in management skills, using Office programs in the theme of using the program and graduating from an institution that provides tourism education in the other theme. It is thought that the research findings will significantly benefit the employees. Keywords: Tourism, Employees, Job Advertisements

Diversity statements signal an organization's culture, values, and commitment to diversity and inclusion. Yet, diversity statements are often perceived as somewhat superficial "boilerplate" or basic statements created to comply with employment equity requirements, especially in job advertisements. With the objectives of understanding the presence of diversity statements in job advertisements, differences between types of libraries, and the types of diversity statements and messages contained in these statements, this study analyzed the diversity statements of 50 online job advertisements for Canadian academic librarian and archivist positions. Four types of diversity statements were identified from this study: Type 1) boilerplate; Type 2) employment equity; Type 3) diversity; and Type 4) expanded diversity management. Findings suggest most Association of Research Libraries (ARL) member institutions in Canada have expanded diversity management statements. Other findings around land acknowledgements, gender identity, and sexual orientation and others are discussed. Recommendations for further studies are included.

This project investigates the structure and development of data science in the Swiss labour market. In general, data science has gained significant importance in the labour market in recent years, which is reflected in an increasing number of job offers for data scientists. Synchronously, data science is framed in the general discussion primarily by means of economic interpretations, such as the diagnosis of a severe shortage of skilled workers.
Companies and other organisations address specific profiles of job seekers through job advertisements for data scientists in the labour market. Through such discursive practices, formats and materializations, the various actors formulate field-specific perspectives on what constitutes "data science" for them. The analysis of job advertisements for Data Scientists makes it possible to analyse the constructions by different actors from a macroscopic point of view, but also to work out commonalities and differences between the fields involved.
The data basis for the study is formed by job advertisements for data scientists, which were collected on a Swiss online job platform using web scraping methods. This resulted in an extensive corpus of text documents (N=4341), which are analysed using topic modelling, a computer linguistic method.

Machine learning algorithms handle numerous forms of data in real-world intelligent systems. With the advancement in technology and rigorous use of social media platforms, many job seekers and recruiters are actively working online. However, due to data and privacy breaches, one can become the target of perilous activates. The agencies and fraudsters entice the job seekers by using numerous methods, sources coming from virtual job-supplying websites. We aim to reduce the quantity of such fake and fraudulent attempts by providing predictions using Machine Learning. In our proposed approach, multiple classification models are used for better detection. This paper also presents different classifiers' performance and compares results to enhance the results through various techniques for realistic results.