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Abstract
Diversity Atlas provides real-time analytic insight into granular cultural and demographic diversity data to help organizations understand the diverse richness of their teams, which accurately reflects humanity’s rich cultural diversity. Diversity Atlas enables organizations to collect data that can transform the way an organization measures, understands, acknowledges and acts on its diversity, inclusion and equity (ID&E) strategies.
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Abstract
Even a decade ago, the field of Diversity Equity and Inclusion—as a field and as a specific job title—did not exist. Today, the field has hit an apex—likely as a result of the corporate zeitgeist with the “business case” for diversity consistently in the forefront of business news, demonstrating organisations with diverse workforces are more innovative, more profitable and have better staff retention. This research study aims to provide a comprehensive understanding of Diversity, Equity and Inclusion (DEI) practitioners in Australia by analyzing LinkedIn profiles. The study examines career patterns, job titles, industry distribution, and gender representation among DEI officers. Using a dataset of 1000 profiles, we investigate average employment durations, career shifts, and part-time DI roles. Our research utilizes descriptive statistics and visualizations to highlight key insights. By leveraging LinkedIn data, we enhance insights into the roles, tenure, and impact of DEI practitioners, contributing to a deeper understanding of this field’s dynamics.
Authors
Nicole Lee, Rezza Moieni & Peter Mousaferiadis
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Abstract
This research paper explores the role of language in shaping cultural and social attitudes towards gender and the importance of using gender-inclusive language to promote gender equality and eliminate gender bias. Specifically, we analysed the Victorian government website in Australia https://www.vic.gov.au/ over some years from 1970-2023 to Measure and compare the evolution of its language across this period in terms of gender neutrality. To conduct this research, we created three datasets by scraping data from three different websites. The first two datasets comprise a list of masculine and feminine words used in the English language, while the third dataset comprises a list of gender-neutral words approved by the Victorian government. We compared this list of words with the data provided by the Victorian government website, and based on this analysis, we assessed how gender-neutral the website was. The findings show that using gender-inclusive language is a powerful way to promote gender equality and eliminate gender bias. Moreover, our analysis reveals that the Victorian government website has become more gender-neutral over the years, which signals their commitment to promoting gender equality and inclusivity. Overall, our research underscores the importance of using gender-inclusive language in all communication, including website content, to create a more inclusive and equitable society.
Authors
Arushi Raichur, Nicole Lee & Rezza Moieni
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Abstract
There are discussions about the importance of diversity in literature and in the media and minimizing gaps between minorities and majorities. In order to see if a community is making progress in minimizing these gaps and to measure success, there is an interest in being able to predict the diversity of communities given currently prevailing. There are well-designed data forecasting algorithms in data science using large data sets. However, diversity data has only been collected over the last few decades. This paper adopts algorithms formulated by Grey and ARIMA (Auto-Regressive Integrated Moving Average), using small data to predict the likely diversity of a cohort for a time in the near future. Our results demonstrate there is more confident forecasting for “country of birth”, but in terms of predicting linguistic and religious diversity, due to the changeable nature of these factors throughout an individual’s life, we would require further data to make any accurate prediction.
Authors
Rezza Moieni, Peter Mousaferiadis & Leyla Roohi
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Abstract
There are discussions about the importance of diversity in literature and in the media and minimizing gaps between minorities and majorities. In order to see if a community is making progress in minimizing these gaps and to measure success, there is an interest in being able to predict the diversity of communities given currently prevailing. There are well-designed data forecasting algorithms in data science using large data sets. However, diversity data has only been collected over the last few decades. This paper adopts algorithms formulated by Grey and ARIMA (Auto-Regressive Integrated Moving Average), using small data to predict the likely diversity of a cohort for a time in the near future. Our results demonstrate there is more confident forecasting for “country of birth”, but in terms of predicting linguistic and religious diversity, due to the changeable nature of these factors throughout an individual’s life, we would require further data to make any accurate prediction.
Authors
Rezza Moieni, Peter Mousaferiadis & Leyla Roohi
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Abstract
For diversity to serve as a competitive advantage and for companies to be successful, the diversity of their workforce should be synchronized with the community they are doing business in. This degree of similarity in diversity of an organisation to its customer base is termed as Mutuality. High synchronization builds a healthy relationship between an organisation and its customers leads to better customer service, thus, radically improve their business performance. However, at present, this concept of diversity & mutuality has been analytically neglected and most organisations in both the public and private sectors are grappling with this aspect. Thus, the goal of this research is to design an empirical formula for the Mutuality Index by using the method of cosine similarity which captures the orientation (the angle) of one attribute of diversity in an organisation with its customer base and determines the similarity between them. The research explains how this data-driven approach can help organisations become better at measuring, understanding, tracking and delivering more informed and better diversity strategies which eventually enhances their business performance and induces a stronger bottom line (Profits)
Authors
Rezza Moieni, Peter Mousaferiadis & Prateek Pateel
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