Background

“[G]atekeepers—funders, project officers, editors, peer reviewers, federal agencies, and others—can play an important role in enforcing a racial equity lens in the work they fund and publish because of the amount of influence they have on researchers’ careers ” (Schwabish and Feng, 2021).

Scholarly communication is often defined as “the system through which research and other scholarly writings are created, evaluated for quality, disseminated to the scholarly community, and preserved for future use” (ACRL Scholarly Communications Committee, 2018). It is meant to serve the public and advance the pursuit of knowledge. It is important that this is done in a way that includes the whole- not just of scholarly communication itself, but of society.

The purpose of these guidelines is to help all authors, editors, and reviewers recognize the use of language and images that are inclusive and culturally sensitive. The guidelines will serve as a global tool and educational resource that can be used by individuals, institutions, and publishers. By addressing the various forms of bias and discrimination currently found in published research, the intent of these guidelines is to set an industry standard that promotes proactive inclusive communication going forward.

Implicit bias

Inclusion is the act or state of comprising part of a whole, making everyone feel valued and important (Merriam-Webster, Rozaki). This should be done intentionally because everyone has biases that they may not be aware of. Oftentimes people think of bias as something conscious. While explicit bias can be overt and intentional, implicit bias is unconscious or hidden. People are unaware of their implicit biases, and they are therefore involuntary and unintentional (Anti-Defamation League).

Bias	an inclination or preference either for or against an individual or group that interferes with impartial judgment
Explicit bias	the conscious attitudes, stereotypes, and overt intentional actions (positive or negative) toward members of a group merely because of their membership in that group
Implicit bias	the unconscious attitudes, stereotypes, and unintentional actions (positive or negative) towards members of a group merely because of their membership in that group

Schwabish and Feng note that the biases a person has “influence the decisions made during a research project, such as the questions that are asked, how data are gathered, how findings are interpreted, and who the main audience is for the work.” Researchers and authors can examine their own biases and determine how these might affect their work. So too can other stakeholders involved in the publishing process, whether they are colleagues, editors, or peer reviewers (Schwabish). By taking the time to examine the potential biases existing in their own work as well as the work of others, researchers and authors can help to make the world of scholarly communication more inclusive.

See the Resources section for a list of tools that can help identify implicit biases.

References

ACRL Scholarly Communications Committee. (2018, August 2). Principles and strategies for the reform of scholarly communication. Association of College & Research Libraries. https://www.ala.org/acrl/publications/whitepapers/principlesstrategies

Anti-Defamation League. (n.d.). Implicit bias. https://www.adl.org/education/educator-resources/lesson-plans/implicit-bias

Implicit bias, unconscious bias. (2016, June 2). Diversity Style Guide. https://www.diversitystyleguide.com/glossary/implicit-bias-unconscious-bias/

Inclusion definition and meaning. (n.d.). The Merriam-Webster.Com Dictionary. https://www.merriam-webster.com/dictionary/inclusion

Powell, J. A. R. A. A. (n.d.). Act, Communicating, Implicit Bias. Racial Equity Tools. https://www.racialequitytools.org/resources/act/communicating/implicit-bias

Rozaki, E., Kovačić, V., Charalampous, N., González, R. L., & Gabriels, W. (2020). Inclusive Communication Manual. Erasmus Student Network AISBL. https://siem-project.eu/documents/ESN_Inclusive_Communication_Manual.pdf

Schwabish, J., & Feng, A. (2021, September). Do no harm guide: Applying equity awareness in data visualization. Urban Institute. https://www.urban.org/research/publication/do-no-harm-guide-applying-equity-awareness-data-visualization

Introduction

Background

Implicit bias

References