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This work deals with social representations of gender equality in the workplace. Little academic work deals with the way workers define gender equality. My research also deals with the implications of this definition in terms of policy implementation.

This work is based on a mixed-method approach. A quantitative study based on an online survey conducted in 2015 at a French company is mobilized to identify and measure the main representations of gender equality among the workers. Then, a qualitative study is used to explore these representations in depth and to examine how they influence the implementation of policy on gender equality.

This work shows that for French workers, equal pay and equal access to responsibilities are the most important dimensions of gender equality, while gender diversity and work-life balance seem less important. The representation of gender equality varies according to gender, professional field and managerial status. These variations help to understand the difficulty of implementing such policy.

Managerially, these results would strongly indicate that companies in France, but also in other developed countries, should consider carrying out awareness campaigns aimed at employees in order to promote a common culture and definition of gender equality. Indeed, the coexistence of various representations of gender equality partly explains the insufficient implementation—and thus the poor performance and general effectiveness of gender equality policies, both in theoretical and practical terms. Companies should also consider introducing awareness campaigns that specifically target men, who grant less importance to gender equality than women.

This study deals with social representations of gender equality in France, a subject which has been largely neglected or overlooked in existing fields of gender research. The international literature on gender equality shows that variations in representations of gender equality constitute a major subject for research and policies about gender, whatever the country. However, this topic still remains inadequately addressed. This research aims to strengthen such research literature dedicated to the issue of gender equality.

The literature on HR metrics does not address the political issues that surround the definition and interpretation of these metrics. However, the need for agreement about HR metrics between different stakeholders is underlined by the framework of the sociology of quantification. This research aims to complement the literature on HR metrics by studying the process of defining and interpreting appropriate HR metrics, focusing on the example of the gender pay gap.

A case study with interviews and participant observation is conducted on a French company.

The results show that HR metrics are essential to prove the existence of inequalities. However, there are disagreements between management, unions and gender equality referents concerning appropriate HR metrics and their use.

Contrary to the literature on the subject, which remains predominantly positivist and normative, this article sheds light on the political issues surrounding the definition and use of HR metrics and shows the importance of involving a range of actors (managers, unions and employees) in the entire process.

With a focus on the evolution of human resource management (HRM) quantification over 2000–2020, this study addresses the following questions: (1) What are the data sources used to quantify HRM? (2) What are the methods used to quantify HRM? (3) What are the objectives of HRM quantification? (4) What are the representations of quantification in HRM?

This study is based on an integrative synthesis of 94 published peer-reviewed empirical and non-empirical articles on the use of quantification in HRM. It uses the theoretical framework of the sociology of quantification.

The analysis shows that there have been several changes in HRM quantification over 2000–2020 in terms of data sources, methods and objectives. Meanwhile, representations of quantification have evolved relatively little; it is still considered as a tool, and this ignores the possible conflicts and subjectivity associated with the use of quantification.

This literature review addresses the use of quantification in HRM in general and is thus larger in scope than previous reviews. Notably, it brings forth new insights on possible differences between the main uses of quantification in HRM, as well as on artificial intelligence and algorithms in HRM.