Preprint / Version 2

The Publication Facts Label: Ascertaining a Publication’s Adherence to Scholarly Standards




Journal integrity, sscholarly communication, publishing platforms


This is a case study of a digital innovation aimed at increasing researchers’, professionals’, and the general public’s ability to approach research publications with a ready method of checking its compliance with the features that set scholarly publishing apart from other sources of information. More specifically, the innovation consists of generating a “publication facts label” (PFL) for articles and journals, which records their adherence to eight elements that reflect scholarly publishing standards. The label conveys data and links for publisher identity, scholarly editorial oversight, article acceptance rates, journal indexing, expert peer review, competing interests, data availability, and research funding (Fig. 1). The PFL is modeled on the United States nutrition facts label that, since 1996, has appeared on food products, proving itself an effective science communication strategy with adoptions around the world in different formats (Christof et al., 2018; Post et al., 2010). At this point, the PFL is being developed as an open source software project by the Public Knowledge Project (PKP) at Simon Fraser University for use with its Open Journal Systems. In this case study, we present the rationale, design, and assessment strategies involved in PFL development and piloting. Although the PFL is still at an early stage, we consider the lessons already learned from this approach worth introducing into the industry’s current emphasis on ways to improve research integrity.


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09/12/2023 — Updated on 12/07/2023


How to Cite

Willinsky, J., & Pimentel, D. (2023). The Publication Facts Label: Ascertaining a Publication’s Adherence to Scholarly Standards. In SciELO Preprints. (Original work published 2023)


Applied Social Sciences


Version justification

Fixed error in two of the images and added minor details.
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    • This paper does not involve the collecting or analyzing of data.