How we build the data

Where our numbers come from

Every figure on Meridian is surfaced from the same dataset the app uses — not written by hand, not generated by an AI. Here is exactly how each one is derived, and where you can check it yourself.

Students working in a university library reading room

Sourced, not authored

Numbers are read straight from the shared dataset and shown as-stored. No language model writes a fact.

Confidence is capped

Risk confidence never exceeds 92% — we don’t imply a certainty we don’t have.

Neutral by design

The public site never knows or infers where you’re from. Personalization happens inside the app, from a profile you fill in.

Traceable and dated

Every figure links to its official source and carries the date it was last reviewed.

Cost of living

How we estimate monthly costs

Each destination shows a monthly living-cost band, broken into rent, food, transport and other across lifestyle tiers. These come from the shared living_costs dataset — the exact records the app’s budget tool reads — so the web and the app never disagree.

Figures are surfaced as stored: no hand-entered numbers, no AI estimation. The country pages show a coarse band; the decomposition shows where the money actually goes.

Basis: Numbeo + Expatistan cost indices, shown per lifestyle tier (economic / moderate / comfortable). See it in context on any destination page.

Country risk score

How the risk score is calculated

The score is a weighted blend of three signals — the weighting reflects what actually disrupts a student’s year:

40%Recent news & safety
35%Currency stability
25%Visa processing
Safe
0–29
Caution
30–54
High
55–79
Critical
80–100
Two honest limits. Confidence in any score is capped at 92% — never 100%. And the score you see on the public site is a neutral global baseline; the app personalizes it to your origin country, because currency exposure depends on where you’re from.

Full explainer: What is the country risk score? Sources are cited per country on each destination page.

How comparisons work

How we pick the “leader” in a comparison

On comparison pages, each row flags the stronger destination for that metric — lower cost, faster visa, longer post-study work, higher QS rank, safer score. The flag is a direct read of the two numbers, nothing more.

One row is deliberately not flagged: acceptance rate. A higher rate means more open, a lower rate more selective — neither is universally “better,” so we show both and let you decide. Comparison prose is generated from the metrics; we don’t editorialize about a country.

All comparison metrics are nationality-neutral — no origin-relative figures appear on the public site.

Scholarship data

How we tier scholarship sources

Each scholarship carries a provenance tier — how official the source is. This describes where the listing came from; it is not a verification of the amount, the deadline, or that you’ll qualify.

Tier 1 · OfficialStraight from the awarding body or a government source.
Tier 2 · SecondaryA reputable aggregator or institution, not the primary source.
Tier 3 · ListedAppears in a broader listing; confirm every detail before relying on it.

Every scholarship links to its official page. Always confirm the current amount and deadline there — figures move. Browse them on the scholarships explorer.

Kept current. Dataset facts carry a last-reviewed date on each destination and scholarship. This methodology was last reconciled with the data model on 2026-07-12 — when a weighting or tier changes in the product, it changes here the same day.

Hero photo: University of Miskolc Library reading room (Szalax, CC0).

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The public site stays neutral. ATLAS applies your budget, field and origin to give personalized matches and a risk score tuned to you — free in the app, from a profile you fill in.