The claim should never be bigger than the evidence.
Knwdle Observatory publishes education data stories for students, families, and curious readers. Our starting point is a question a reader can use, followed by a comparison they can inspect.
Sources before conclusions
We prefer primary statistical releases and institution-level sources. A story identifies the dataset version, reporting period, selected population, and definitions behind its chart. A release date and a reporting year are recorded separately.
A visible method
We explain selection, exclusions, missing observations, and calculations. A selected group of colleges is labeled as that group. An unweighted institutional average is not presented as a student-weighted national statistic. We avoid comparing measures from different cohorts as though they describe the same students.
Useful comparisons, bounded claims
Historical patterns are observations. They are not a promise about a future admission outcome, aid award, or salary. When data cannot answer a question, the story says so. An association alone does not establish why something happened.
Authorship and corrections
Stories credited to the Knwdle research desk are organizational work. We do not attach invented expert credentials or reviewer identities. Each article has a publication date, an update date, and an updates section. Material changes to a conclusion should be described there.
Reuse and attribution
Where we provide a source-data extract, use its identifiers and provenance to check the analysis. Consult the original provider’s terms before redistributing upstream datasets. Attribute a Knwdle analysis by linking to the story and its methodology.
Found a problem? Contact Knwdle with the claim, source, and calculation you checked.