Background

PlainRecalls is a independent data-journalism portal that analyzes product recalls using public data from agencies such as FDA, CPSC, and NHTSA. Recall records are ingested programmatically from official agency APIs; the team writes and reviews the guides, methodology, and editorial commentary while maintaining independence by not accepting payment from entities it covers. This approach provides reliable, neutral insights into recall trends and their implications for consumers.

Editorial approach

The PlainRecalls Editorial editorial process follows PlainRecalls's Editorial Standards for Data Journalism. Every dataset we cover is traced back to its originating public source, and we publish the provenance of each statistic on the page so readers can verify it independently. We do not accept compensation, sponsorship, or influence from entities we cover.

When we present derived numbers (rankings, ratios, comparisons), the methodology page documents exactly how the figure was computed. If a number cannot be computed consistently across every entity in the dataset, we either disclose the gap or omit the comparison rather than present misleading data.

How content is produced

Data ingestion and computation are handled by deterministic pipelines — every numeric value, ranking, and ratio shown on a data page comes directly from the upstream source agency, unmodified. Numbers are never estimated or interpolated. Where we draw data from a primary public dataset, the figure is reproduced exactly as the source published it, and the originating dataset is named and dated on the page. The plain-language summaries and explanations that surround those figures are generated from the source data to help readers interpret it, while the figures themselves are computed directly from the source by the pipeline, not hand-entered.

Source attribution is shown on every page; the methodology underlying any derived figure is documented at the link above. We follow the guidance of Google Search Central's Helpful Content principles — write for readers, document sources, and disclose the editorial process — and welcome any factual flag at the contact link below.

Corrections and feedback

If you find an error, stale figure, or missing context on any page we publish, please use the contact page or write to hello@plainrecalls.com with the URL and the issue. We aim to respond within 72 hours and to publish corrections with a visible revision note.

Areas of focus

• product recalls
• recall data
• public dataset analysis

Contact and identity

• Email: hello@plainrecalls.com
• Publisher: https://plainrecalls.com