The Unjournal
The Unjournal

For Evaluators

Get paid for expert peer review. Your evaluations are published and citable—real credit for review work.

Why Evaluate for The Unjournal?

Unlike traditional journals where peer review is unpaid, anonymous, and invisible, The Unjournal compensates evaluators, publishes their work openly, and gives them proper academic credit.

Paid Work

Our current base compensation is $100 for a completed evaluation. We agree the scope, timing, and payment before anyone commits.

Published & Citable

Your evaluation receives a DOI and is published in The Unjournal (ISSN 3071-2173) on PubPub. Real scholarly credit for review work.

Prize Opportunities

In 2024-25, we awarded $6,500 in evaluator prizes. Future prize rounds depend on funding.

Signed or Anonymous

Choose whether to sign your evaluation publicly or remain anonymous. Your choice, every time.

Flexible Timeline

We work with your schedule. Most evaluations take 3-6 weeks, but we accommodate busy periods.

Impactful Research

Evaluate research that matters—work informing global health, development, policy, and effective interventions.

Compensation

$100 current base compensation for a completed evaluation Policy updated September 11, 2026

At present, $100 is the compensation we can guarantee for a completed evaluation. We have historically aimed for at least $450 average compensation per evaluation, and met that target in earlier funded cycles through base payments, incentives, and prizes. With more funding, we aim to return to that level and increase compensation where scarce expertise or a particularly demanding assignment warrants it.

Future evaluator prizes depend on funding. If a new prize round is funded, eligible evaluations completed before the funding decision may be considered retrospectively, but prizes and their amounts are not guaranteed.

Our longer-term compensation approach includes:

Previous prize round: In 2024-25, we recognized outstanding evaluations with $6,500 in prizes and public acknowledgment. See our 2024-25 prize winners. This was a funded historical round, not a guarantee of future prizes.

How It Works

1

Join Our Pool

Complete a simple form with your expertise areas and background. We'll add you to our evaluator database.

2

Receive Invitations

When we have research matching your expertise, we'll reach out with details and timeline. You can accept or decline.

3

Conduct Your Evaluation

Review the research using our structured guidelines. Provide written feedback and quantitative ratings across multiple dimensions.

4

Publication & Payment

Your evaluation is published on PubPub with a DOI. Payment is processed promptly after submission.

What we ask of evaluators: Provide substantive, constructive feedback that helps authors improve their work. Rate research across dimensions like methodological rigor, real-world relevance, and contribution to the field. Be thorough but fair.

Evaluation Forms

Our evaluation process uses structured forms to ensure consistency and thoroughness. Evaluators can use either the newer interactive form or the relevant Coda form, unless their evaluation manager gives paper-specific instructions. If you opened the wrong stream, switch between academic and applied below.


Evaluator Guidelines

Before submitting an evaluation, please read the full evaluator guidelines. They explain what we ask evaluators to assess, how to interpret the rating scales, and how the academic and applied streams differ.

Read the full guidelines here

If the embedded page is hard to read, open the full guidelines in GitBook.


AI Tools in Evaluation

The Unjournal supports evaluators using AI tools thoughtfully as a complement to, not a substitute for, expert human judgment. We are developing infrastructure to provide AI-generated reviews and consistency checks to evaluators after they submit, so they can compare perspectives and flag any important points they may have missed.

Working policy (April 2026; still evolving, not all aspects formally confirmed): Evaluators may use AI tools selectively. Appropriate uses include looking up or clarifying content in the paper, or running extensive checks that are not feasible to do by hand; in that case the AI-assisted part should appear separately (in a dedicated section, link, or footnote), with at least a hand-checked sample. We encourage evaluators not to use AI tools for the overall evaluation or for the ratings and predictions. Please link to your AI chats where possible and identify any text generated by LLMs. You must stand by everything in your report as your own judgment, and we expect at least 8 hours of human work, over and above any time the AI tools take.
Recent evidence: A large-scale survey of AAAI-26 authors and program committee members found that participants not only found AI reviews useful, but actually preferred them to human reviews on key dimensions such as technical accuracy and research suggestions (Biswas et al., 2025). This offers some promise for AI-assisted peer review, and informs how we are developing our own approach.

Full details: our AI/LLM use policy for evaluators.


Who We're Looking For

We seek evaluators with expertise in quantitative research methods and relevant subject areas. Ideal candidates have:

✓ PhD or equivalent research experience
✓ Expertise in economics, psychology, policy, or related quantitative fields
✓ Track record of published research
✓ Commitment to constructive, substantive feedback
✓ Interest in global priorities research
✓ Ability to assess methodological rigor

Focus Areas

We particularly need evaluators with expertise in:

Join Our Evaluator Pool

Complete a short form to be added to our database. We'll reach out when we have research matching your expertise.

Apply to Evaluate Evaluator Guidelines