Fact check: What is the methodology behind factually.co's fact-checking process?

1. Why the direct answer is missing and what that matters

The source set provided contains summaries and excerpts describing other fact‑checking organizations but does not contain any material explicitly detailing factually.co’s procedures, so any claim about that organization’s methodology cannot be established from these inputs ^{[1] [2] [3]}. This absence matters because methodological transparency is the core of evaluating fact‑checking credibility; without a primary description from factually.co or independent reporting about its workflow, readers cannot verify whether it follows industry norms such as sourcing, verification, corrections policy, or transparency declarations. The documents we do have instead offer proxy models and best‑practice templates from peer organizations that illustrate plausible approaches to rigorous fact‑checking ^{[4] [5]}.

2. What Factchequeado’s model shows about community‑focused verification

Factchequeado emphasizes a collaborative, community‑oriented approach tailored to Latino and Hispanic audiences in the United States, centered on empowering communities through fact‑checked content and media literacy tools, with a predominantly Latino women journalist team ^[1]. Their model highlights active collaboration across networks and an outreach emphasis—practices that increase cultural and linguistic accuracy when checking claims affecting specific communities. If factually.co serves niche audiences, adopting similar methods would address context sensitivity and trust building: local sourcing, multilingual verification, and partnerships with community organs are core elements reflected in the provided material ^[1].

3. GIJN’s three‑checkpoint system: a model for investigative rigor

The GIJN guide presents a structured three‑checkpoint system—start‑up meetings to challenge hypotheses, midpoint reviews to surface quality issues, and intensive fact‑checking sessions to verify claims—designed specifically for investigative journalism ^[4]. This framework enshrines iterative scrutiny, cross‑verification, and editorial oversight, with scheduled checkpoints reducing confirmation bias and catching methodological gaps before publication. Organizations seeking high assurance commonly adopt such staged review practices, making GIJN’s approach a useful comparator for assessing whether an entity like factually.co follows similarly rigorous, documented procedures ^[4].

4. Full Fact’s institutional monitoring and capacity‑building perspective

Full Fact’s methodology focuses on systematic monitoring of public claims, evidence‑based adjudication, and public training in media literacy and data skills ^[5]. Their work illustrates how a fact‑checking body can combine reactive checking (responding to viral claims) with proactive monitoring of institutional promises and data. Important features include transparent sourcing, clear verdicts, and public correction mechanisms. If factually.co follows such institutional practices, one would expect documented monitoring protocols, publication of sources, and accessible correction policies—none of which appear in the provided excerpts ^[5].

5. Factiverse and FactiSearch: tech‑enabled verification without method details

The materials on Factiverse describe research‑based AI tools and a comprehensive database of fact‑checks intended to support credibility and risk mitigation, but they do not specify human workflows or editorial standards ^[3]. Automated tools can accelerate claim detection and cross‑reference existing checks, yet they must be paired with human judgement and documented editorial policies to avoid automation errors. The presence of such technology in the source set suggests that modern fact‑checking practice often blends AI with human review, but again, no evidence links factiverse tools to factually.co, nor do the summaries reveal how decisions are vetted or published in those systems ^[3].

6. Comparison and synthesis: common features across documented models

Across the provided models, common methodological features emerge: collaborative verification and community engagement, staged editorial review for investigative pieces, institutional monitoring and correction mechanisms, and the use of technological tools to surface claims and aggregate prior fact‑checks ^{[1] [4] [5] [3]}. These recurring elements form a plausible template for responsible fact‑checking organizations. However, the crucial missing piece in the dataset is direct, dated documentation from factually.co confirming which of these practices it employs, when it adopted them, and how it documents sourcing and corrections ^[1].

7. What to request next to close the evidence gap

To determine factually.co’s methodology authoritatively, request or locate dated methodology documentation, editorial policy pages, published correction policies, and examples of processed fact‑checks from factually.co itself; corroborate with independent reporting or third‑party audits. The current source set dates range from 2025‑09 to 2026‑06 and describe analogous organizations, but they do not provide the firm data needed to state factually.co’s methods. Obtaining primary materials will allow direct comparison to the models summarized here and reveal whether factually.co follows community‑centered, checkpointed investigation, institutional monitoring, AI‑assisted workflows, or a hybrid approach ^{[1] [4] [5]}.