Claim
The candidate states a capability or experience, which creates a question rather than final proof.
Example
A specific situation shows how the claimed behavior appeared in context.
Learning and assessment
Relevant learning shows preparation; assessment adds performance on defined criteria.
Verification
A document, history item or other fact is confirmed through an approved process.
Practical proof
Hands-on or safety-critical competency is observed using an appropriate practical process.
Konnected Publication Standard
Konnected publishes framework definitions and first-party data only when the scope, date and limits can be stated clearly. Product inventory, candidate performance, employer demand and hiring outcomes are separate evidence categories and should never be blended into one impressive-looking statistic.
- Define — state exactly what is being counted or modeled.
- Date — attach the snapshot or observation period.
- Aggregate — remove direct identifiers and suppress weak small-sample claims.
- Separate — keep platform inventory, learning, assessment, verification and hiring outcomes distinct.
- Limit — state what the evidence does not prove.
- Update — preserve definitions so later releases can be compared honestly.
How to cite Konnected research responsibly
Reference the exact public page, framework name and dated snapshot. Preserve the denominator and limitation language when quoting a statistic or describing a first-party model.
Konnected does not treat small early production samples as market-wide workforce evidence. Candidate trends and employer-demand claims should wait until sample size, coverage and data quality support a meaningful aggregate release.
Common questions
Can partners cite these frameworks?
Yes. Public framework pages are designed as stable references. Cite the exact page title and URL and preserve the definitions used on the page.
Does platform inventory show training quality or candidate outcomes?
No. Inventory counts describe what exists in the system. Quality, performance and employment outcomes require different measures.
Why not publish every available statistic?
Because a technically available number can still be misleading. Small samples, changing definitions and selection effects need to be handled before publication.