AARC is proud to support Academic Analytics’ recent statement on the use of quantitative information in promotion and tenure decisions. Our research at AARC seeks to emphasize the humanity of researchers, and to underscore that the people who produce research are separate from – and greater than – the quantified representation of their research outputs. We echo the below points from the Academic Analytics position statement:

1. The use of verifiable quantitative data in promotion and tenure is only one important indicator of a scholar’s productivity and must be supplemented with other kinds of information and with more nuanced indicators of quality.

2. Faculty members should have access to the research metrics used in promotion decisions about them, and they should have the opportunity to correct and supplement that record prior to any substantive review.

3. No database of research output is a comprehensive record of scholarly achievement. Journal articles, books, chapters, grant information, conference proceedings, and patents are traditional modes of research dissemination in many disciplines and often become bibliometric artifacts easily included in databases. But other modes of dissemination (e.g., exhibitions, storytelling, performances, choreography, musical composition, zine authorship, blog authorship, dataset production, software programs, opensource materials, public domain contributions, and media mentions) are valued in many disciplines. These venues are not captured in most databases, potentially disadvantaging scholars whose work is most often shared in those forms. Such gaps should be recognized and accounted for in evaluation processes.

4. Because research cultures vary widely across the disciplines, and even sub-disciplines (e.g., relative prominence of articles or books or conference proceedings; co-authorship vs. single authored work), administrative reviewers of faculty scholarship need to develop an informed understanding of realistic expectations for the disciplines under review.

5. Because the quantity of one’s research output does not equate to the quality and impact of a scholar’s research output, other means for evaluating significance, quality, and importance to the field of study should complement quantitative measures.

6. Research metrics cannot account for systemic biases or personal and social factors that may influence one’s research. Gender, racial, ethnic, mental health, disability, and age biases in the American academy are increasingly well-documented and may impact the venue, quantity (but not necessarily the quality) of output.

Please read the original position statement here: https://academicanalytics.com/wp-content/uploads/2021/12/Academic-Analytics-Promotion-Tenure-.pdf