Bias in Peer Review: 8 Types, Examples & Solutions

Bias in Peer Review: 8 Types, Examples, Causes, and How to Reduce It

Peer review is designed to help academic journals evaluate research fairly and maintain scientific quality. However, reviewers and editors are human, and their judgments can sometimes be influenced by factors unrelated to a manuscript's scientific merit.

Bias in peer review occurs when characteristics such as an author's reputation, institutional affiliation, gender, geographic location, or a reviewer's personal preferences influence the evaluation of academic research.

Some forms of bias are conscious, while others may arise unintentionally through assumptions, professional relationships, or established disciplinary expectations.

These influences can affect which reviewers are invited, how manuscripts are assessed, and how editorial decisions are made.

Although research has documented bias-related concerns in scholarly publishing, evidence varies across disciplines and study designs. Not every difference in acceptance rates proves that discrimination occurred.

This article explains eight important types of peer review bias, provides practical examples, examines relevant research findings, and outlines strategies journals and researchers can use to promote fairer manuscript evaluation.

What Is Bias in Peer Review?

Peer review bias refers to a systematic or potentially unfair influence on manuscript evaluation that is unrelated to the quality or relevance of the submitted research.

Ideally, reviewers assess a paper according to its research question, originality, methodology, evidence, analysis, and conclusions.

A biased assessment may instead be influenced by information about the authors or the reviewer's own expectations.

For example, a reviewer might unconsciously assume that a manuscript from a prestigious university is more reliable than comparable research from a lesser-known institution.

Similarly, a reviewer may favor findings that support an established theory while applying unusually strict standards to contradictory results.

Bias can occur at different stages of the publication process, including editorial screening, reviewer selection, expert assessment, and final decision-making.

Recognizing these possibilities is important because fair evaluation depends on applying relevant scientific criteria consistently.

Why Does Bias Occur in Peer Review?

Bias can arise from several interacting factors.

Researchers develop expertise within particular academic communities, and their professional experiences influence how they interpret evidence.

Reviewers may also have existing relationships with authors, strong methodological preferences, or expectations about which findings are likely to be correct.

Sometimes journal procedures expose reviewers to identifying details that can trigger assumptions about reputation or institutional status.

Editorial workloads and limited reviewer availability may also lead journals to rely repeatedly on familiar networks.

These factors do not mean that every reviewer behaves unfairly.

Rather, they show why even experienced academics benefit from structured evaluation criteria, conflict-of-interest policies, and appropriate editorial oversight.

8 Types of Bias in Peer Review

Different forms of bias can affect scholarly evaluation in different ways.

The following categories overlap, and a single manuscript review may involve more than one potential influence.

1. Gender Bias

Gender bias occurs when perceptions or assumptions about an author's gender affect how research is evaluated or how reviewers are selected.

For example, a reviewer might unconsciously make different assumptions about the expertise of two researchers based on their perceived gender.

Gender-related patterns can also occur before manuscript evaluation.

Editors may rely on professional networks that disproportionately include reviewers of a particular gender.

A study titled Gender Bias in Scholarly Peer Review examined information about approximately 9,000 editors and 43,000 reviewers from the Frontiers journal series. It found that women were underrepresented in the review process and documented same-gender preferences in reviewer selection.

However, findings about manuscript decisions are not uniform.

A separate large-scale study involving 145 scholarly journals did not find that the peer-review and editorial processes examined systematically disadvantaged manuscripts authored by women.

These results illustrate an important distinction: gender imbalances in reviewer participation and gender bias in manuscript acceptance are related but different questions.

2. Institutional Prestige Bias

Institutional prestige bias occurs when the reputation of an author's university or research institution influences an assessment.

Reviewers may assume that research from highly ranked institutions is more credible, even before evaluating its methods.

For example, imagine two manuscripts reporting comparable scientific findings.

One is affiliated with an internationally recognized university, while the other comes from a smaller regional institution.

If reviewers apply different standards because of those affiliations rather than research quality, institutional prestige bias may be present.

A systematic review of geographic bias identified experimental evidence that institutional reputation can influence scholarly evaluation under certain conditions.

However, the available experimental evidence was limited, so findings should not be generalized to every journal or discipline.

3. Geographic Bias

Geographic bias involves evaluating research differently because of an author's country, region, or location.

It may overlap with perceptions of institutional prestige, research funding, language proficiency, or scientific infrastructure.

For example, reviewers might assume that a study conducted in a low-income country is less rigorous without carefully examining its actual methodology.

A separate concern arises when research addressing a local or regional problem is considered unimportant merely because the issue is unfamiliar to reviewers elsewhere.

Geographic relevance should be assessed in relation to the journal's scope and the study's contribution, not unsupported assumptions about where the research originated.

Research has identified examples of geographic influence in scholarly assessment, but the strength and consistency of these effects require further investigation.

4. Confirmation Bias

Confirmation bias occurs when reviewers favor evidence that supports their existing beliefs and scrutinize conflicting evidence more harshly.

This issue is especially important in disciplines where researchers disagree about established theories, analytical methods, or competing explanations.

Consider a reviewer who strongly supports a particular theory of student learning.

If a manuscript reports findings that challenge that theory, the reviewer may focus disproportionately on possible weaknesses while overlooking similar limitations in supporting studies.

Appropriate scientific skepticism is not itself bias.

Reviewers are expected to question evidence.

The problem arises when comparable methodological standards are applied inconsistently because of the direction of the findings.

A fair review should assess research quality regardless of whether the results confirm or challenge the reviewer's expectations.

5. Publication or Outcome Bias

Publication-related bias can occur when certain research findings are considered more attractive for publication than others.

For example, journals may prefer statistically significant, positive, surprising, or novel findings over well-designed studies reporting null results.

This broader publication bias is not identical to reviewer bias, because decisions can also be influenced by editorial priorities, submission patterns, and publication policies.

Nevertheless, reviewers may contribute if they consistently describe null findings as unimportant without assessing their scientific value.

A carefully conducted study that finds no evidence of an expected effect can still make a meaningful research contribution.

Reviewers should distinguish the significance of a research question from whether its results are statistically significant or align with expectations.

6. Methodological Bias

Methodological bias occurs when reviewers unfairly favor certain research approaches or reject alternatives without sufficient justification.

For instance, a reviewer experienced primarily in quantitative methods might criticize a qualitative study because it does not include statistical hypothesis testing.

Such criticism would be inappropriate if statistical testing is unrelated to the study's research design.

Similarly, a reviewer may dismiss an observational study simply because it is not a randomized trial, even when randomization would be impractical or unethical.

Different research questions require different methods.

A fair evaluation should examine whether the selected methodology is suitable for the stated objectives and whether the authors have applied it rigorously.

Reviewers may still identify genuine methodological limitations, but their criticisms should be based on the manuscript's requirements rather than personal preferences.

7. Professional Relationship and Conflict-of-Interest Bias

Bias may arise when reviewers have personal, financial, or professional interests connected to the authors or research outcomes.

Potential conflicts include recent collaborations, academic rivalries, close personal relationships, and financial interests.

For example, a reviewer working on a competing project may have an incentive to delay or criticize similar research.

Conversely, a reviewer may assess a close collaborator's manuscript too favorably.

The presence of a professional relationship does not automatically prove biased conduct.

However, relevant conflicts should be disclosed so editors can determine whether the reviewer can provide an independent assessment.

The Committee on Publication Ethics recommends that reviewers declare potential conflicts and maintain objectivity throughout the review process.

8. Language and Communication Bias

Language-related bias can occur when reviewers confuse writing proficiency with the scientific quality of a study.

Academic manuscripts require clear communication, and substantial language problems can legitimately prevent readers from understanding methods or results.

However, reviewers should distinguish between genuine ambiguity and minor language imperfections.

For example, a manuscript written by researchers who use English as an additional language might contain grammatical errors while presenting scientifically sound methods and evidence.

A fair reviewer should identify language improvements without allowing minor wording issues to overshadow the scientific contribution.

At the same time, reviewers should not ignore language problems that materially change the interpretation of results.

The appropriate goal is clear reporting and consistent evaluation standards.

Examples of Bias in Peer Review

The following hypothetical scenarios illustrate how different biases might appear during manuscript evaluation.

These examples describe possible mechanisms, not proof that a particular unfavorable review was biased.

What Does Research Say About Peer Review Bias?

Research into peer review bias has produced important but sometimes conflicting findings.

One study examining reviewer appointments across Frontiers journals identified gender imbalances and same-gender preferences in reviewer selection.

A much larger investigation covering 145 journals examined reviewer selection, recommendations, and editorial decisions. It did not find systematic disadvantage for women-authored manuscripts within the processes and journals studied.

Research has also explored geographic and institutional prestige effects.

A systematic review of controlled studies found evidence of such effects in some settings, but noted that the limited number of eligible experiments prevented broad conclusions.

Studies comparing single-anonymous and double-anonymous peer review have likewise reported mixed results.

These findings suggest that peer-review fairness cannot be evaluated using one universal assumption.

Results may vary according to discipline, journal, manuscript type, reviewer composition, and the specific outcome being studied.

Research should therefore distinguish between reviewer behavior, editorial decisions, and broader differences in publication outcomes.

How Does Bias Affect Scientific Publishing?

Bias can influence academic publishing through several mechanisms.

Unequal Evaluation Standards

When comparable manuscripts are judged differently because of author characteristics or reviewer preferences, publication decisions may become less consistent.

Reduced Opportunities for Researchers

Researchers from less-established institutions or underrepresented academic communities may face barriers if evaluators rely on reputation rather than evidence.

Narrower Scientific Discussion

If reviewers disproportionately favor established theories, unconventional but rigorous findings may encounter unnecessary obstacles.

Loss of Confidence in Publication Decisions

Concerns about unfair assessment can weaken researchers' confidence in editorial procedures.

Inefficient Manuscript Revision

Biased or poorly justified reviewer requests can lead authors to perform unnecessary analyses or revisions.

These are potential consequences, not outcomes that occur in every journal.

Their likelihood depends on the actual review environment and safeguards in place.

How to Reduce Bias in Peer Review: 7 Practical Strategies

No single intervention can eliminate every form of bias.

However, journals and reviewers can use several complementary strategies to improve fairness.

1. Use Double-Anonymous Peer Review Where Appropriate

Double-anonymous review aims to conceal author identities from reviewers.

This may reduce exposure to information about institutional prestige, reputation, or demographic characteristics.

However, anonymity is not always complete.

Reviewers may infer authorship from citations, public preprints, distinctive datasets, or specialized research topics.

Evidence about its effects on bias is also mixed.

Double-anonymous reviewing should therefore be viewed as one possible safeguard rather than a guaranteed solution.

2. Establish Structured Evaluation Criteria

Journals can provide reviewers with clear questions about methodology, originality, analytical validity, reporting, and interpretation.

Structured criteria may help reviewers focus on the scientific features of a manuscript.

For example, instead of asking only whether a paper is impressive, a review form might ask whether its methods adequately address the research question.

Consistency is important, but evaluation standards must remain appropriate to different study designs.

3. Broaden Reviewer Selection

Editors can expand their reviewer networks to include qualified researchers from different institutions, geographic regions, career stages, and research traditions.

This may reduce excessive dependence on a small group of familiar experts.

Reviewer diversity should support, not replace, the requirement for appropriate subject expertise.

Editors must still evaluate conflicts of interest and reviewer qualifications.

4. Provide Reviewer Training

Training can help reviewers recognize common sources of bias and improve their ability to evaluate diverse methodologies.

Useful topics include objective criticism, conflicts of interest, cultural assumptions, research design, and constructive feedback.

Training should encourage reviewers to question whether their judgments reflect manuscript evidence or unsupported expectations.

5. Strengthen Conflict-of-Interest Procedures

Journals should require reviewers to disclose relevant personal, financial, and professional relationships.

Editors can then assess whether a potential conflict is manageable or requires selecting another reviewer.

Clear disclosure procedures reduce uncertainty and support independent assessment.

6. Monitor Editorial Decisions

Journals can examine patterns in reviewer invitations, report recommendations, revision requests, and publication decisions.

Where appropriate and lawful, aggregated analyses may help identify disparities requiring further investigation.

However, differences in outcomes do not automatically establish discrimination.

Editorial analysis should consider relevant factors such as manuscript types, disciplines, study quality, and submission patterns.

7. Encourage Evidence-Based Reviewer Comments

Reviewers should explain why a particular concern affects scientific quality.

For example, instead of stating that a paper is unsuitable because it uses an unfamiliar method, a reviewer should identify a specific limitation of that method in relation to the research question.

Editors should challenge unsupported criticism and avoid allowing one reviewer's personal preferences to determine the outcome.

Can Double-Blind Peer Review Eliminate Bias?

Double-blind peer review, more commonly called double-anonymous peer review, is designed to conceal author identities during manuscript evaluation.

This approach can limit some information that might influence reviewers.

However, its effectiveness depends on whether the identities remain hidden and which type of bias is being addressed.

A systematic review comparing anonymous review models identified variation in outcomes across the studies examined.

Other research has reported associations between double-anonymous review selection and publication outcomes that may reflect differences between authors or submissions rather than the effects of anonymity itself.

Therefore, double-anonymous review should not be presented as a proven universal solution to bias.

A comprehensive fairness strategy also requires objective reviewer selection, appropriate evaluation criteria, conflict management, and editorial oversight.

How Can Reviewers Recognize Their Own Bias?

Reviewers can improve the fairness of their assessments by examining how they reach judgments.

Before completing a review, consider the following questions:

• Am I evaluating the evidence or relying on the authors' reputations?
• Would I apply the same methodological standards if the findings supported a different conclusion?
• Am I criticizing an approach because it is unsuitable or merely unfamiliar?
• Do I have a professional relationship or competing interest that should be disclosed?
• Are my comments specific enough to justify the concerns I have raised?
• Am I distinguishing scientific limitations from language or formatting issues?
• Have I identified meaningful strengths as well as weaknesses?

These questions encourage reflective judgment without assuming that every criticism is biased.

What Should Authors Do if They Suspect Reviewer Bias?

Authors who believe a review may contain bias should respond professionally and focus on identifiable problems.

First, separate scientific criticism from comments that may reflect unsupported assumptions.

If a reviewer makes inaccurate factual claims, explain the issue with evidence.

For example, an author may demonstrate that a requested methodological analysis is inappropriate for the study design.

If the report contains personal remarks, discriminatory language, or an undisclosed conflict of interest, the author can raise the concern with the journal editor.

An appeal or response should describe the specific issue rather than accusing the reviewer of misconduct without evidence.

Editors may clarify the report, invite another reviewer, or reconsider the evaluation according to journal procedures.

A negative recommendation alone is not sufficient evidence of bias.

Frequently Asked Questions About Bias in Peer Review

What is bias in peer review?

Bias in peer review occurs when factors unrelated to a manuscript's scientific quality influence how the research is evaluated, which reviewers are selected, or what editorial decisions are made.

What are the main types of peer review bias?

Common categories include gender bias, institutional prestige bias, geographic bias, confirmation bias, methodological bias, outcome bias, language bias, and conflicts of interest.

Does gender bias exist in peer review?

Some studies have identified gender-related imbalances in reviewer selection, while research on manuscript evaluation and acceptance has produced mixed findings. The results depend on the context and outcome examined.

How can journals reduce bias in peer review?

Journals can use structured evaluation criteria, improve reviewer diversity, manage conflicts of interest, provide reviewer training, monitor editorial patterns, and consider appropriate anonymity models.

Is double-blind peer review unbiased?

No. Double-anonymous review aims to reduce some identity-related influences, but reviewers may still infer authorship or be affected by other biases.

What is confirmation bias in scientific peer review?

Confirmation bias occurs when reviewers favor findings supporting their existing beliefs and apply different standards to studies reporting contradictory results.

Can peer reviewers be biased without realizing it?

Yes. Unconscious assumptions about author reputation, research methods, or expected findings can influence evaluations even when reviewers intend to be fair.

What should an author do about an unfair peer review?

Authors should identify the specific concern, provide evidence in their response, and contact the journal editor if the review appears to contain unsupported, inappropriate, or discriminatory criticism.

Conclusion

Bias in peer review is an important concern because scholarly publishing depends on fair, independent, and evidence-based manuscript evaluation.

Potential influences include author reputation, institutional prestige, geographic location, gender, methodological preferences, and professional conflicts.

However, research findings differ across journals and disciplines, and unequal outcomes do not automatically prove biased conduct.

Reducing these risks requires multiple safeguards, including appropriate reviewer selection, structured evaluation criteria, conflict-of-interest management, reviewer training, and editorial accountability.

By focusing consistently on scientific evidence and applying fair standards, reviewers and editors can strengthen the credibility of academic publishing and support a more inclusive research environment.