Every AI-generated answer in Social Explorer includes a Sources panel that shows exactly where the data comes from. This panel ensures full transparency by listing the dataset, table, geographic level, year, and citation details used to produce the result. The goal is to make every answer verifiable and easy to trace back to its official source.
The Sources panel appears alongside the numeric result and is automatically generated for each query. It allows users to understand not only the numbers they are seeing but also how the AI selected the underlying dataset.
What the Sources Panel Includes
Dataset Name
The panel identifies the exact dataset used, such as ACS 2022 5-Year, ACS 2021 1-Year, Decennial Census 2020, RCMS 2020 Religion, HUD Housing data, FBI Crime statistics, EASI projections, or any other dataset available in Social Explorer’s library.
Table and Variable Details
The panel lists the specific ACS or Census table code and the variables extracted. For example, an ACS query may reference the table “B01003 - Total Population” or “B19013 - Median Household Income.” This gives users clear visibility into which variables were used to calculate the result.
Geographic Level
The panel specifies the exact geographic layer applied, such as state, county, city, census tract, block group, ZIP Code Tabulation Area (ZCTA), or congressional district. This helps users confirm that the results reflect the correct geographic resolution.
Year of Data
The displayed year reflects the most recent available data that matches the user’s request and the dataset’s publication schedule. The Sources panel makes this explicit so users always know which year the estimates represent.
Methodology Notes
Some datasets include additional methodological context, for example, whether the values come from ACS 5-year pooled estimates, modeled EASI projections, or Decennial Census full counts. If ACS margins of error or ZCTA approximations apply, the panel notes this clearly.
<datasources> Metadata Block
Every answer includes a machine-readable <datasources> block that encodes the dataset, table, and variable information. This block allows other tools, APIs, and automated workflows to programmatically reproduce or verify the result.
Why the Sources Panel Matters
The Sources panel makes every AI answer transparent, reproducible, and academically credible. Users can trace each value back to the original source, understand dataset limitations, and ensure that the selected dataset aligns with their analytical goals. Whether the query involves a single estimate or a multi-geography comparison, the Sources panel guarantees that the research process remains fully documented and verifiable.