Formal women-only networks: literature review and propositions

© 2017, © Emerald Publishing Limited. Purpose: The purpose of this paper is to review the emerging literature on formal women-only business networks and outline propositions to develop this under-theorised area of knowledge and stimulate future research. Design/methodology/approach: The authors review the existing literature on formal internal and external women-only networks and use the broader social capital and network literature to frame their arguments and develop propositions. Findings: Propositions are developed regarding how both internal and external formal women-only business networks can be of value for members, firms/organisations and the wider social group of women in business. Research limitations/implications: The authors focus on the distinction between external and internal formal women-only networks while also acknowledging the broader diversity that can characterise such networks. Their review provides the reader with an insight into the state of the art and a set of propositions that present opportunities for future research. Practical implications: The paper provides insights into how women in business, organisations and wider society can leverage value from both internal and external formal women-only business networks. Social implications: The paper contributes to research showing that the social structure of interactions and context can impact women’s standing in the workplace. Originality/value: The paper sheds light on the under-studied and under-theorised phenomenon of formal women-only business networks. Beyond the individual member level, the authors suggest that such networks can be of value for organisations and the wider social group of women in management and leadership positions

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Feminism in women’s business networks: A freedom-centred perspective

Copyright © The Author(s) 2022. How do women’s business networks help to advance women’s freedom? Drawing on Zerilli’s freedom-centred feminism, our study sets out to answer this question at the intersection of freedom, feminism and work. Critics argue that women’s business networks promote a postfeminist view of freedom focusing on individual self-realisation and thus participate in rolling back collective, feminist efforts to dismantle structural inequalities. We reconceptualise women’s business networks as political arenas and argue that making claims about shared interests and concerns in such an arena constitutes a feminist practice of freedom. With an original, inductive and qualitative research design combining topic modeling and dialectical analysis, we examine the claims made in 1529 posts across four women’s business network blogs. We identify postfeminist claims and new forms of change and transformation that can help to advance women’s freedom across three ‘dialectics of freedom’: conformity and imagination; performative care and relational care; sameness and openness. Our findings show that uncertain and contradictory ways of defining and engaging with women’s freedom can emerge through claim-making in such arenas. The fragility of the process and its outcomes are, then, what can move feminism forward at work and beyond

Beyond nostalgia: Identity work in corporate alumni networks

© The Author(s) 2015. Although corporate alumni networks are a developing practice, academia has said very little about them and their members. In this article, our goal is to provide an account of how members of such networks construct themselves as alumni. To that end, we adopt a narrative approach to identity construction and empirically explore the identity work that the members of one corporate alumni network carry out in order to sustain their identification with a past organizational setting. Our case study leads us to document four ‘identity stratagems’ (Jenkins, 1996) through which members incorporate elements of their past professional experience into their self-narratives: nostalgia, reproduction, validation and combination. It thus allows for a better understanding of corporate alumni networks and their members, while also contributing to the broader identity literature by further documenting how organizational participants can incorporate elements of a past professional experience into their self-narratives

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed