BIAS Word inventory for work and employment diversity, (in)equality and inclusivity (Version 1.0)

The language used in job advertisements contains explicit and implicit cues, which signal employers’ preferences for candidates of certain ascribed characteristics, such as gender and ethnicity/race. To capture such biases in language use, existing word inventories have focused predominantly on gender and are based on general perceptions of the ‘masculine’ or ‘feminine’ orientations of specific words and socio-psychological understandings of ‘agentic’ and ‘communal’ traits. Nevertheless, these approaches are limited to gender and they do not consider the specific contexts in which the language is used. To address these limitations, we have developed the first comprehensive word inventory for work and employment diversity, (in)equality, and inclusivity that builds on a number of conceptual and methodological innovations. The BIAS Word Inventory was developed as part of our work in an international, interdisciplinary project – BIAS: Responsible AI for Labour Market Equality – in Canada and the United Kingdom (UK). Conceptually, we rely on a sociological approach that is attuned to various documented causes and correlates of inequalities related to gender, sexuality, ethnicity/race, immigration and family statuses in the labour market context. Methodologically, we rely on ‘expert’ coding of actual job advertisements in Canada and the UK, as well as iterative cycles of inter-rater verification. Our inventory is particularly suited for studying labour market inequalities, as it reflects the language used to describe job postings, and the inventory takes account of cues at various dimensions, including explicit and implicit cues associated with gender, ethnicity, citizenship and immigration statuses, role specifications, equality, equity and inclusivity policies and pledges, work-family policies, and workplace context.

Typecasting in the Recruitment of Full Professors

The recruitment of full professors is critical for the formation of academia. The professorship is critical not only for the prosperity of the HEIs, but especially so for the establishment, development and communication of the discipline. In this chapter, we analyze the initial step of the typecasting process in the recruitment of full professors. We use a few cases to illustrate how the intellectual and social organization of the field of education science(s) is manifested in publicly posted job advertisements. The analysis shows that the field is characterized by heterogeneity and no longer has a basis in one single discipline. New relations between research, teaching, and society can be observed, as well as a narrowing of authority of the professorship but an increase of responsibilities.

The Gender-Biased Wording of Recruitment Advertisements in Iraq

This research studies the nature and the scope of gender discrimination in job advertisements across Iraq’s various business sectors, segments, and hierarchical levels. It also attempts to understand the correlation between the language of the vacancy announcements and the level of the gender discriminatory content in them. This study is conducted with the hope of contributing to gender equality at the workplace in Iraq and the wider region. The current study adopts a content coding and analysis method that depends on the analysis of job advertisements (n=1015) by organizations operating in Iraq published in the leading recruitment websites and social media pages for a period of about four consecutive months from June to October 2017. The analysis is conducted using descriptive statistics and tested using simple cross tabulation method. Although the topic has been studied in various countries and contexts, it lacks academic attention in the Middle East, which can be seen as a unique area for research. Also, this research is the first attempt, as far as we are aware of, to comprehend the correlation between the choice of language (English, Arabic or Kurdish) and gender-biased wording of vacancy announcements. Understanding the relationship between language and gender discrimination in job advertisements might as well unveil a new area of study and aid in the quest for gender equality in the Iraqi workplace. This paper provides scientific evidence that more than 41% of all job advertisements in Iraq commit gender discrimination. The majority of them indirectly favor male candidates. Additionally, the nature of the vacancies for which women are preferred is different from the ones that target men. The adverts generally try to segregate women into non-managerial and administrative jobs. The study also infers a statistically significant correlation between the language of the advertisement and gender discrimination rate.

The Gap between Higher Business Education and Business Expectations: The Case of Poland

Employers expect business school graduates to possess a wide and diverse range of competencies, because the conditions governing the operations of enterprises are subject to constant and dynamic change. Therefore, adjusting study programs to labor market requirements is one of the main challenges faced by higher education institutions, particularly business schools. Therefore, the expectations of potential employers have become an object of detailed study for most universities. The most frequently applied research approach adopted for such studies involves direct surveys of employer opinions, based on various types of questionnaires. An alternative method is textual analysis of job advertisements using analytical tools that automate the research process. The aim of this article is to identify the gap between the business education offer and the expectations of the labor market in Poland, as well as to show the possibility of using the analysis of the contents of job advertisements to identify employer expectations regarding the competencies of university graduates. The presented research is exploratory in nature, with four questions posed by the authors during the research process. The research is innovative with regard to Poland and in relation to graduates of business schools.

Requirements for Project Managers—What Do Job Advertisements Say?

The growing number of projects and the key role of project managers in their implementation makes the competencies of managers a subject of many studies. An attempt can be made to determine the project manager competencies that employers appreciate the most through analyses of job advertisements. Due to a very large number of job advertisements, it may be difficult or even impossible to analyze their content manually. A solution may be to fetch and process job advertisements automatically. The main purpose of this paper was to identify the project manager competencies that are the most desired by employers. An analysis of job advertisements was performed to identify the project manager competencies required by employers. Job advertisements were automatically downloaded from online job boards. Fragments of job advertisements that described requirements were analyzed with text mining. The analysis included preprocessing, building of corpora of documents, construction of document-term matrices, application of traditional data mining methods, and Latent Dirichlet Allocation (LDA), which is a popular topic modeling algorithm. After the initial text processing (all characters except letters were removed, uppercase letters were converted to lowercase letters, words deemed useless were removed, and words were converted to their basic form), n-grams were built, and topics identified with LDA were generated. The most frequently used words and n-grams, along with the identified topics, were graphically represented. The meanings of the words and sentences were not analyzed in the text mining analysis of the job advertisements. The analysis did not take into account whether the words appeared side by side in the document-except for the intentional creation of n-grams (such as “communication skill”). The analysis, however, facilitated the identification of certain patterns and regularities in the occurrence of specific strings in the documents (fragments of advertisements describing the requirements). The interpretation of the results is based on the frequency of words and n-grams and frequency of words in topics identified by the LDA algorithm. This paper contributes to science by showing that text mining of job offers can, to some extent, help determine project manager competencies in demand. The method can be used by organizations training future project managers to modify and better adapt curricula to the needs of the labor market. It can be used to monitor the current trends in project manager requirements as well.

Constructions of the ideal elite employee: A content analysis of job advertisements for positions in the Norwegian upper class

Previous research has shown that the upper class has a high degree of self-recruitment. Simultaneously, research on job recruitment suggests that there has been an increase in the importance of ‘soft skills’. This article investigates the connection between these two phenomena by looking at elite employers’ constructions of ‘the ideal employee’ and how this may contribute to class reproduction. By analysing 150 advertisement texts linked to positions in the upper class and fractions within it (the cultural, professional and economic upper classes), it explores which qualifications and characteristics are required. The analysis indicates that ‘soft skills’ play a substantial role in recruitment in all upper-class fractions, suggesting that ‘hard skills’ do not suffice to achieve an upper-class position. Indeed, the fact that many of the personal characteristics are linked to modes of being typical of an upper-class habitus makes it harder for people from lower in the class structure to match the description of the ‘ideal candidate’. Furthermore, this article finds the following three distinct employee types: the authoritative leader is idealized in the economic fraction, the dedicated worker in the professional fraction and the coaching leader in the cultural fraction. This article also points to examples of gender stereotyping that may function as contributing factors in reproducing occupational segregation.