An original data report from True Jobs · Updated June 2026
Most commentary about the job market relies on what companies say they are hiring for. We can offer a different vantage point: what the listings themselves actually look like once you score every one for legitimacy. The figures below are computed live from the True Jobs dataset of listings aggregated from more than 20 sources and run through our Realness Score. No personal data, no individual listings — just the aggregate picture job seekers rarely get to see.
Every scored listing falls into one of three legitimacy bands. Here is how the entire dataset breaks down:
96.9% of scored listings (253) showed strong legitimacy signals — a verifiable employer, a fresh posting, a specific description, and a trustworthy source. 3.1% (8) landed in the mixed band, where a quick independent check is warranted before you invest time. And 0.0% (0) carried weak or concerning signals: stale postings, anonymous "companies," template descriptions, or implausible pay.
The practical takeaway for a job seeker is stark. If you apply blindly down a results page, a meaningful fraction of your effort is spent on listings that were never going to lead anywhere. Triaging by legitimacy is not optional optimization — on these numbers, it is the difference between an efficient search and a demoralizing one.
Work mode is one of the first filters most job seekers apply, so it is worth knowing whether legitimacy varies across remote, hybrid, and on-site roles in our dataset:
| Work mode | Listings scored | Avg. Realness Score |
|---|---|---|
| Onsite | 181 | 76.6 |
| Remote | 71 | 76.6 |
| Hybrid | 9 | 78.2 |
Differences across work modes tend to reflect who is posting and how: categories that attract more reposted or pipeline-building listings drag their averages down, while roles posted directly by employers to fill an immediate need score higher. Use the averages as context, not as a reason to avoid an entire category — a high-scoring remote role still beats a low-scoring on-site one.
Only 0.0% of scored listings disclosed any salary information. Beyond being a fairness issue, missing pay data is also a mild legitimacy signal: genuine employers filling a real role are increasingly willing to state a range, while pipeline and bait listings rarely bother. When you do see a salary, sanity-check it — pay that is wildly above or below the market for the role is one of the clearest scam indicators we track.
This report regenerates from live data. Read the full Realness Score methodology, learn how to spot fake listings yourself, or browse scored jobs now.