Single-Blind vs. Double-Blind Peer Review at Academic Conferences: Which Should Your Event Use?
When a conference call for papers goes out, one of the least visible but most consequential decisions has already been made behind the scenes: which peer review model the program committee will use. Single-blind, double-blind, and open review each shape who gets a fair hearing, how quickly decisions come back, and how candid reviewers are willing to be. This guide focuses specifically on that choice for conferences — not journals, which run on different timelines and reviewer pools — and lays out the trade-offs organizers need to weigh before locking in a submission system.
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Last updated: July 2026 • Reviewed by the NeucitePress Editorial Board • Reading time: 8 minutes
If you’re looking for a step-by-step walkthrough of how conference peer review works from submission to decision, see our companion piece on the peer review process for conference papers. Here, we go one level deeper into a decision program chairs face every cycle: which anonymization model to adopt, and why the “right” answer differs by field and by conference.
The Three Models of Conference Peer Review
Conference peer review generally follows one of three anonymization models. Each answers a different question: should reviewers know who wrote the paper, should authors know who is judging it, and should anyone outside that circle see the exchange at all?
Single-Blind (Single-Anonymous) Review
In single-blind review, reviewers can see the authors’ names and affiliations, but authors do not learn who reviewed their submission. This is the traditional model at many engineering and applied-science conferences, largely because it is simple to administer — there is no need to strip identifying details from a submission before it goes out for review.
Double-Blind (Double-Anonymous) Review
Double-blind review hides both directions: reviewers do not see author names or affiliations, and authors never learn who reviewed them. Authors must anonymize their own manuscripts — removing identifying citations, funding acknowledgments, and institutional references — before submission. Program committees using this model typically build anonymization checks into their submission workflow.
Open Review
Open review removes some or all of the anonymity in either direction. Some conferences publish reviewer identities alongside their comments; others go further and post the submitted paper, the reviews, and the author rebuttal publicly, sometimes before a final accept or reject decision is even made. Machine learning conferences that use platforms built around open commentary have popularized this model over the past decade.
Single-Blind Review: Strengths and Limitations
Single-blind review remains common because it is the path of least administrative resistance, but that simplicity comes with trade-offs.
Strengths:
- Simple to run — there is no anonymization step for authors to get wrong or for organizers to verify.
- Reviewers can weigh a paper against an author’s or lab’s track record, which can be useful in small subfields with only a handful of active research groups.
- Faster to set up in submission software, since no redaction workflow or identity-scrubbing check is required.
Limitations:
- Leaves room for reputation bias — well-known authors or prestigious institutions may receive more benefit of the doubt from reviewers.
- Can disadvantage early-career researchers and authors from less prominent institutions, a concern raised repeatedly in discussions of review fairness.
- Reviewers may be more reluctant to critique senior figures they recognize in a small, close-knit field.
Double-Blind Review: Strengths and Limitations
Strengths:
- Reduces the influence of author reputation, institutional prestige, and name recognition on the initial read.
- Encourages reviewers to evaluate the submission on its methodology and contribution rather than its authorship.
- Widely viewed as fairer for early-career and first-time conference authors, since it levels the playing field on the first pass.
Limitations:
- Anonymization is imperfect — self-citations, unique datasets, distinctive writing style, or very niche subfields can make authors identifiable anyway.
- Adds administrative overhead: program committees must check submissions for identifying information before assigning reviewers.
- Authors sometimes over-scrub papers, stripping out useful context such as prior related work, to stay safely anonymous.
Open Review: Strengths and Limitations
Strengths:
- Full transparency — readers can see exactly what reviewers said and how authors responded.
- Creates a public record that remains useful after publication, supporting reproducibility and meta-research on the field itself.
- Can improve reviewer accountability, since comments are attributed or at least visible to the community.
Limitations:
- Reviewers may soften criticism if their name will be publicly attached, particularly toward senior or influential authors.
- Not well suited to fields where being visibly wrong as a reviewer carries professional risk.
- Requires reviewer buy-in; some experienced reviewers decline to participate in fully open models.
Which Model Fits Which Field and Conference Type
| Field / Conference Type | Commonly Used Model | Why |
|---|---|---|
| Computer science & machine learning | Double-blind or open | Large, fast-moving, competitive fields where reputation bias is a recognized concern; open review platforms largely originated here. |
| Electrical & electronics engineering | Single-blind | Long-standing convention in many society-run conferences, plus smaller subfields where full anonymization is difficult to enforce. |
| Clinical & biomedical conferences | Single-blind, sometimes double-blind for abstracts | Specialist reviewer pools are often small enough that true anonymity is hard to preserve regardless of the stated model. |
| Humanities & regional/discipline-specific conferences | Varies, often single-blind | Reviewer pools can be small enough that anonymization offers limited practical benefit. |
| Interdisciplinary & emerging-field conferences | Increasingly open | No entrenched convention yet, giving early organizers room to set new norms for transparency. |
None of this is fixed. Program committees change models between years as their community’s expectations shift, and some conferences run hybrid approaches — double-blind for the initial review with an optional open rebuttal period, for example.
Practical Implementation Guidance for Conference Organizers
Match Your Submission System to Your Model
Conference management systems differ in how well they support each model. Some platforms have built-in anonymization checks and conflict-of-interest matching, while others handle open commentary and public rebuttal threads more natively. Confirm your chosen system supports your model before you finalize your call for papers, not after submissions start arriving.
Write Explicit Anonymization Instructions
If you’re running double-blind review, give authors a concrete checklist: remove names and affiliations from the title page and headers, cite your own prior work in the third person (e.g., “[Author names], 2023” rather than “our previous work”), omit or generalize identifying funding acknowledgments, and strip identifying metadata from the submitted PDF file itself.
Screen for Conflicts of Interest Regardless of Model
Conflict-of-interest screening matters under every model, not just open review — reviewers can often guess authorship even under double-blind conditions, especially in small fields, so a COI declaration step should not be skipped just because the model is anonymized.
Build Your Timeline Around the Model You Choose
Double-blind review adds time for anonymization checks and potential desk rejections for policy violations. Open review adds time for a public comment or rebuttal window. Build these steps into your review calendar rather than treating them as an afterthought squeezed between submission deadline and notification date.
A Decision Framework for Conference Organizers
Before locking in a review model for your event, work through these questions with your program committee:
- How large and how well-networked is your author and reviewer pool? Smaller fields get less practical benefit from double-blind anonymization.
- Has your field already converged on a norm your authors will expect? Deviating from convention without explanation can create confusion or resistance.
- How much administrative capacity does your program committee have for anonymization checks or open-review moderation?
- Do you want a public, citable record of the review exchange itself, or is that better kept internal to the committee?
- Would your typical reviewers be willing to sign their names to their comments, or would that discourage participation?
FAQ
What is the difference between single-blind and double-blind peer review at conferences?
In single-blind review, reviewers know the authors’ identities but authors do not know their reviewers. In double-blind review, neither side knows the other’s identity, and authors must anonymize their manuscripts before submission.
Is open review used at academic conferences?
Yes, particularly in computer science and machine learning, where some conferences publish submissions, reviews, and author rebuttals publicly as part of the review process.
Which review model reduces bias the most?
Double-blind review is generally considered the strongest safeguard against reputation and institutional bias, though it cannot fully eliminate the risk of authors being identified through writing style or self-citation.
Can a conference switch peer review models between years?
Yes, and many do as community expectations evolve. Organizers should announce the change clearly in the call for papers so authors can prepare submissions correctly.
Do double-blind conferences still have reviewer bias?
Some bias can persist because anonymization is imperfect, but double-blind review is still associated with a more level initial evaluation than single-blind review in most studies of the practice.
Sources
- Committee on Publication Ethics (COPE) — peer review ethics guidelines
- OpenReview — open peer review platform used by academic conferences
- IEEE Author Center — conference and journal peer review resources
- ACM Publications — policies on anonymous and open review
- EasyChair — conference management system supporting blind review workflows
