Annual-Report-2024 - Flipbook - Page 84
Moderator Pernilla Wittung-Stafshede
Selecting and Training Reviewers
• Provide training sessions for reviewers on recognizing
and mitigating unconscious bias. Nudge the reviewer: Reminder of common biases in proximity to marking grids.
• Explicitly outline priorities and expected outcomes of
funding call to reviewers. Describe profiles of successful
target candidates.
• Avoid using reviewers that have direct or indirect connections with the applicants. Recruiting international
(foreign) reviewers to broaden the view and help ensure proposals are evaluated strictly on scientific merit.
• Increasing the number of potential reviewers invited
to review to ensure suitable and matched reviewers for
each proposal. To reduce work for expert reviewers and
provide a broader perspective, introduce early-career
expert reviewers on review panels.
• Strive for diversity (not only gender) among reviewers
and review panel members.
Reviewing
• Reviewers’ comments must be sufficiently precise so
that the applicant can address them. The reasons for a
low score should be provided.
82 | Connecting Bright Minds
• Require review panel members to document individual
scores before group discussion to avoid dominance of
a single member. Transparency in scores given by all
panel members. Justify marks with a short explanation.
A well-designed scoring grid of how/what to assess in
each stage of the selection.
• Reviewers should be instructed not to assign undue
importance to language errors in applications. Establish systematic, clear evaluation standards that prioritize research, relevance, and originality over language
accuracy.
• Providing an opportunity for factual clarification or
context from applicants could help ensure reviews are
based on accurate understanding of the proposed work.
• Create a channel of communication between applicants
and reviewers. The applicant should have a possibility to respond to criticism and, in return, the reviewer
should have an opportunity to modify the review.
• As it is practically impossible to distinguish fundable
projects within a small window around a hard cutoff,
a certain percentage of applications below and above
the cutoff point, that fall within the uncertainty/resolution, are chosen randomly.
