The glass ceiling in NLP

By Natalie Schluter. 2018

22 citations recorded by the source corpus.

In this paper, we provide empirical evidence based on a rigourously studied mathematical model for bi-populated networks, that a glass ceiling within the field of NLP has developed since the mid 2000s.

Subfields: Communication, Statistical and Nonlinear Physics, Natural Language Processing, AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

In Statistical and Nonlinear Physics

In Natural Language Processing

In AI Ethics, Fairness & Society

Citations in the corpus

On Measuring Social Biases in Sentence Encoders (2019, background): “5 See Schluter (2018) for a recent exposition of the glass ceiling in the NLP research community.”
Mitigating Gender Bias in Natural Language Processing: Literature Review (2019, methodology): “A few interdisciplinary studies (Herbelot et al., 2012; Avin et al., 2015; Fu et al., 2016; Schluter, 2018) have emerged, and we urge more interdisciplinary discussions in terms of gender bias.”
Gender Bias in Machine Translation (2021, background): “…countermeasures, engaging with translators (De Marco and Toto, 2019; Lessinger, 2020) and annotators (Waseem, 2016; Geva et al., 2019), and considering everyone’s subjective positionality—and, crucially, also the lack of diversity within technology teams (Schluter, 2018; Waseem et al., 2020).”
The State of NLP Literature: A Diachronic Analysis of the ACL Anthology (2019, background): “…including that on Google Scholar (Khabsa and Giles 2014; Howland 2010; Orduña-Malea et al. 2014; Martín-Martín et al. 2018), on the analysis of NLP papers (Radev et al. 2016; Anderson, McFarland, and Jurafsky 2012; Bird et al. 2008; Schluter 2018; Mariani, ∗ 1200 Montreal Rd., Ottawa, Canada.”
NRC Publications Archive Archives des publications du CNRC (unknown): “…Ordu˜na-Malea et al., 2014; Mart´ın-Mart´ın et al., 2018), on the analysis of NLP papers (Radev et al., 2016; Anderson et al., 2012; Bird et al., 2008; Schluter, 2018; Mariani et al., 2018; Qazvinian et al., 2013; Te-ich, 2010; Saggion et al., 2017), on citation intent (Aya et al., 2005; Teufel…”
Unsupervised Discovery of Implicit Gender Bias (2020, background): “Despite widespread documentation of the negative impacts of bias, stereotypes, and prejudice (Krieger, 1990; Goldin, 1990; Steele and Aronson, 1995; Logel et al., 2009; Schluter, 2018), these concepts remain difficult to define and identify, especially for non-experts.”