Published On: Wed, Nov 30th, 2022

Addressing the Bias in the Grant Awards System

In a perfect world, grants would fund science that puts patients first, resource allocation would be based on scientific merit alone, and grant reviewers would focus on innovation rather than awards and prestige. In the real world, however, the system of writing and reviewing grants is flawed. Applicants are bogged down with hours of procedures, and reviewers are biased by an unfair process. At 1907 Foundation, we addressed these issues by reinventing the entire grant management system to be more efficient, more ethical, and more equitable.

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Grant applications take scientists and doctors away from research

Everyone wants funding, but no one wants to wade through the bureaucratic red tape involved. Organizations with enough money hire professional grant writers, and for good reason. Simply finding a grant can require hours of research. After that, expect to spend 30 to 50 hours preparing foundation grants, 60 to 80 hours applying for state grants, and up to 120 hours writing complicated federal grants. This all amounts to days upon days of writing for only a 10 percent chance of success

Imagine being one of the world’s most brilliant scientists and begging for money two days out of every week. Studies find that researchers spend over 40 percent of their time applying for grants. Once submitted, the review process can take over seven months. That’s time that would be far better invested in scientific, medical, and technological advancements.

Problems scientists and foundations encounter with the current grant review system 

Many researchers write grant after grant only to watch funding go to the same prestigious institutions. The bulk of resources always seems to flow to a select few. To understand why this happens, you need to understand the peer-review process. 

During the traditional grant selection process, three “expert” reviewers each receive a stack of completed applications. The first glaring problem with this system is right on the top of every application; each resume reveals the applicant’s name and affiliate institution. Reviewers are privy to researchers who collaborated with the applicant, articles the applicant has published, and awards the applicant has received. This information has nothing to do with the idea proposed in the current grant — it serves only to create bias in the reviewers. 

Peer review was supposed to be an unbiased means of allocating resources by putting decisions into the hands of fellow experts. Unfortunately, the process allows an applicant’s network to play a pivotal role. The prestige of applicants’ universities, as well as their rank within the university, department, gender, immigration status, and race often factor into reviewers’ decisions. The scale tends to tip in favor of investigators, institutions, departments, and demographic groups with solid representation.

Often, biased decisions are not made with malice. After all, when reviewers come across a prominent researcher’s name backed by a list of successful projects, it’s tempting to continue that momentum, even if the new proposal is lacking. Experience is important, but ideas need to stand on their own merits, and new researchers need a chance to be heard as well.

In addition to bias, the review process is flawed by small sample size. Given a typcial total of three reviewers, the influence of one biased or conflicted individual has incredible impact. How is a sample of three meaningful?

Automation eliminates bias when selecting grant recipients 

If we want to fix the problem, we must fix the entire system. Atala is a groundbreaking grant management software designed to do just that. It simplifies the grant-writing process, bases funding decisions on science, and gives early-career scientists a fighting chance. 

Atala expands sample size by requiring at least ten people to review each application. If one reviewer needs to excuse themselves for an applicant, they are able to invite another reviewer to take their place to maintain the adequate sample size. Our system reviews the reviewers as well as the applicants. We evaluate conflicts by tracking how much time reviewers spend on applications, their affiliate institutions, and areas of specialty. 

In addition, Atala withholds information prone to create bias until the final round of deliberations. Reviewers approach grants in an initial lightning round, during which they judge only the proposal’s idea. They review the science rather than the scientist. 

Every director on our advisory board reviews applications alone in two rounds before consulting with others. After everyone has considered applications individually, dashboards display the stats and call out differences in opinion. 

Because we streamlined the grant-writing process, we enable scientists to stop chasing funding and focus on their work. Researchers who once devoted 40% of their time to writing proposals can cut that down to 4%. 

In designing Atala, our sole focus was to provide researchers with an easily navigated grant management system. After using the software for a year, we began to think more broadly. Atala disrupts the traditional grant management process by eliminating inadequate sample size, pervasive bias, time waste, complexity, confusion, and unclear reasoning. 

Nonprofit work seeks to put money into the hands of the people who drive progress. Now, at last, we have the automation to accomplish this ethically and equitably.  

Blair Kellly, co-founder, and CTO of 1907 Foundation, is an experienced software developer who wrote and deployed a custom donations platform and created 1907 Foundation’s own grant management software. 

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