Learn to identify and avoid biased language, for example in letters of recommendation, teaching evaluations, etc.
We are all biased. What can we do? The ALBA Declaration on Equity & Inclusion advises to implement unbiased selection, hiring, and assessment, by learning to identify and avoid biased language, for example in letters of recommendation, teaching evaluations, etc. This article provides useful tips & resources on best practices about inclusive language.
Vacancy position descriptions are notoriously biased to indicate the preferred gender by the employer. Letters of recommendations regularly reveal the professor or colleague’s conscious or unconscious bias towards the recommendee, just by language choices and gender-specific expressions.
- Test your own language bias knowledge on the EIGE website.
- Consult your human resource specialists for support on writing job descriptions.
- A Linguistic Comparison of Letters of Recommendation for Male and Female Chemistry and Biochemistry Job Applicants; Schmader et al 2007, U of Arizona (US)
- Evidence that gendered wording in job advertisements exists and sustains gender inequality; APA PsycArticles.
Test your language:
- Test your language bias knowledge: Policy document, job descriptions, legal text; European Institute for Gender Equality (EIGE), (Lithuania)
- Gender bias calculator for gender biases in recommendation letters; Tom Forth, 2013 (UK)
- Gender Decoder for Job Ads
Examples of Best practices:
- Inclusive conferences and events and Pronoun stickers; Equality Diversity and Inclusion in Science and Health EDISgroup (UK)
- Pronoun Usage; University of California Irvine (US)
- Avoiding gender bias in reference writing, CSW Arizona (US)
- New policy allows for name changes in published papers, eLife Latest
- Here’s How Unconscious Racial Bias Can Creep Into Recommendation Letters—and How You Can Avoid It, The muse
- In French: French guidelines for avoiding gender stereotypes (in French); French Republic, Haut conseil à l'égalité entre les femmes et les hommes, 2016 (FR)