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Guide · Metrics Explained

What Are Q1, Q2, Q3, and Q4 Journals? Quartiles Explained

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Evaluating Q1, Q2, Q3, and Q4 journals requires understanding quartile rankings: each subject category is divided into four equal 25% tiers based on citation metric percentiles, allowing objective, field-normalized journal evaluation regardless of whether a discipline naturally exhibits high or low citation velocity.

Q1 Tier Top 25% of Category Percentile: 75.0% – 100%

Q2 Tier Upper-Middle Tier Percentile: 50.0% – 74.9%

Q3 Tier Lower-Middle Tier Percentile: 25.0% – 49.9%

Q4 Tier Bottom 25% Tier Percentile: 0.0% – 24.9%

Figure 1: Standard percentile distribution across academic journal quartiles (Q1 to Q4).
Why Quartiles Matter More Than Raw JIF: A Journal Impact Factor of 3.0 represents a top-tier Q1 placement in Pure Mathematics, but sits in the Q3 or Q4 tier in Oncology. Quartiles normalize for these field-specific citation densities.

Understanding Q1 Q2 Q3 Q4 Journals and Category Percentiles

Within any indexed subject category, journals are ordered by their primary metric value (Clarivate JIF in Journal Citation Reports, or Elsevier CiteScore in Scopus). That ranked list is divided into four equal segments based on percentile rank:

Quartile Tier Percentile Range Category Rank Position Academic Significance
Q1 (First Quartile) 75.0% – 100% Top 25% of journals Highest citation impact and editorial prestige. Heavily prioritized for graduation, tenure, and grant funding.
Q2 (Second Quartile) 50.0% – 74.9% 25th to 50th percentile Solid, reputable disciplinary journals with active scholarly read-rates and consistent peer-review standards.
Q3 (Third Quartile) 25.0% – 49.9% 50th to 75th percentile Regional, specialized, or newer emerging titles with modest average citation accumulation.
Q4 (Fourth Quartile) 0.0% – 24.9% Bottom 25% of journals Lowest relative citation volume in the field; often targeted by early-stage research or specialized niche notes.

How Journal Quartiles Are Calculated

The mathematical rank percentile ($P$) of a journal within a subject category of $N$ journals is determined by its descending rank order ($X$):

$$\text{Percentile } (P) = \frac{N – X + 0.5}{N} \times 100$$

Where:

  • $N$ = Total number of journals indexed within that specific subject category.
  • $X$ = The rank of the target journal (1 being the highest metric score).

If a category contains 120 journals ($N = 120$):

  • Ranks 1 through 30 fall into Q1 (100% to 75%).
  • Ranks 31 through 60 fall into Q2 (74.9% to 50%).
  • Ranks 61 through 90 fall into Q3 (49.9% to 25%).
  • Ranks 91 through 120 fall into Q4 (24.9% to 0%).

Why the Same Journal Can Hold Multiple Quartiles

Authors are often confused when a journal claims to be both “Q1” and “Q2”. This discrepancy occurs for two structural reasons:

1. Multi-Category Indexing

Journals are frequently indexed across multiple subject fields. For example, a journal covering both Biochemistry and Agricultural Sciences competes against two different cohorts of publications:

  • In Agricultural Sciences (a lower-density citation field), a JIF of 4.2 places the journal at rank 8 of 80 → Q1 Tier.
  • In Biochemistry & Molecular Biology (a massive citation field), that same 4.2 JIF places it at rank 150 of 290 → Q2 Tier.

2. JCR (Web of Science) vs. Scopus (CiteScore)

Clarivate and Elsevier use different citation calculation windows and index different journal pools:

  • JCR Quartiles: Calculated using the 2-year Journal Impact Factor across Web of Science Core Collection titles.
  • Scopus Quartiles: Calculated using the 4-year CiteScore across the broader Scopus database.

Because Scopus includes conference proceedings and book chapters while Web of Science uses stricter source criteria, a journal’s competitive rank percentile frequently differs between the two platforms. Read our full comparison on Impact Factor vs. CiteScore and Scopus vs. Web of Science.

How Academic Committees and Funders Use Quartiles

Institutional evaluation committees frequently mandate minimum quartile tiers rather than raw numbers:

  • PhD Graduation Criteria: Many universities require candidates to publish at least one or two Q1 or Q2 papers as first author prior to defending their thesis.
  • Tenure & Faculty Hiring: Evaluation boards utilize Q1 publications as a proxy for peer acceptance and scholarship reach.
  • Government Research Grants: Funding agencies increasingly benchmark applicant publication records against Q1 percentages in their respective subfields.

Step-by-Step: How to Check a Journal’s Quartile

  1. Identify the Primary ISSN: Search using the 8-digit ISSN on Clarivate Master Journal List or Scopus Source Preview to avoid name duplicates.
  2. Inspect Category Breakdown: Identify all subject categories the journal belongs to, and verify which category your manuscript aligns with.
  3. Confirm the Evaluation Year: Always verify the current reporting year; quartile thresholds shift annually as new journals enter the cohort. Follow updates in our JCR 2026 Release Guide.
  4. Cross-Check with Our Tools: You can lookup verified metric records and quartile badges directly in our Journal Lookup Tool.

Key Takeaways

  • Quartiles rank journals relative to peers within the same discipline, not on a universal scale.
  • Q1 represents the top 25% (75th–100th percentile); Q4 represents the bottom 25% (0–24.9th percentile).
  • A journal can hold different quartiles across multiple indexed categories and between JCR and Scopus.
  • Before submitting, verify that the journal’s quartile meets your specific university or funder mandates using our guide to choosing the right journal.

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Reviewed by Umair Abbasi

AI Engineer & Data Scientist | PhD Candidate, Artificial Intelligence

Umair Abbasi is an AI Engineer and Data Scientist with a background in machine learning, AI agents, and MLOps, currently pursuing a PhD in Artificial Intelligence and holding a completed M.S. in Data Science. He leads the data architecture and tooling behind the journal metrics database and comparison tools. As an active researcher navigating journal selection and citation metrics in his own academic work, he brings a practitioner's perspective to how impact factor, CiteScore, and related metrics are actually used β€” not just how they're defined.

Credentials & Expertise:
- M.S., Data Science (completed) - PhD Candidate, Artificial Intelligence (in progress) - Machine Learning Specialization β€” Stanford University (Coursera) - Google Data Analytics Professional Certificate

This article is reviewed for accuracy on a rolling basis. Data on individual journal metrics changes annually with each Clarivate JCR release (typically June) and Scopus CiteScore update (typically June). See our Data Sources & Methodology page for sourcing details.

Written and reviewed by named authors Every page is bylined with real credentials, linked to ORCID or Google Scholar — no anonymous “Team” posts.
Every figure sourced and dated No metric is published without a visible primary source and a “last reviewed” date.