How we measure

What we do not know

A list of the gaps in our own data, published because you will find them anyway.

Every data product has holes. Most vendors leave you to discover theirs. Here are ours, so you can decide whether they matter for what you are doing.

Coverage

  • We do not cover every employer. Sources that restrict automated access are absent, and we do not estimate around the gap.
  • Coverage is uneven by country and by employer size. Smaller employers who post only to a local board are underrepresented.
  • A market where we have thin coverage will produce a plausible-looking median computed from too few postings. The counts are always shown so you can judge.

Salary

  • Only postings that publish a range are included in any salary figure.
  • Disclosure is not random: it skews to regulated markets and larger employers. Medians inherit that skew.
  • We do not convert currencies. A cross-border comparison of our medians compares tax systems as much as pay.

Age and freshness

  • Age is computed from the publication date, not from continuous observation.
  • Republishing resets it, and we cannot always detect that.
  • A listing being visible does not prove the role is open.

Titles and categories

  • Grouping by title is a judgement call. Two people would draw the lines differently.
  • Composite roles land in one bucket.
  • New role names take time to appear in any grouping, including ours.

Intent

We cannot see whether an employer means to hire. Nothing we publish should be read as a claim about intent, and where our pages discuss stale listings they say "signal", not "verdict", deliberately.

Why publish this

Two reasons. A buyer who finds a limitation on their own concludes it was hidden; a buyer who reads it here concludes it was measured. And writing the list down keeps us honest about which gaps we have accepted and which we are still working on.

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If something here is wrong or out of date, tell us and we will fix the post.