Published at MetaROR
November 20, 2024
Table of contents
Curated
Article
Preprint review services: Disrupting the scholarly communication landscape
1. Research on Research Institute (RoRI)
2. Centre for Science and Technology Studies (CWTS), Leiden University
3. Central Library, Lisbon University Medical School
4. Azerbaijan University of Architecture and Construction
5. Information School, University of Sheffield
Originally published on August 11, 2024 at:
Editors
Kathryn Zeiler
Kathryn Zeiler
Editorial Assessment
by Kathryn Zeiler
The authors present a descriptive analysis of preprint review services. The analysis focuses on the services’ relative characteristics and differences in preprint review management. The authors conclude that such services have the potential to improve the traditional peer review process. Two metaresearchers reviewed the article. They note that the background section and literature review are current and appropriate, the methods used to search for preprint servers are generally sound and sufficiently detailed to allow for reproduction, and the discussion related to anonymizing articles and reviews during the review process is useful. The reviewers also offered suggestions for improvement. They point to terminology that could be clarified. They suggest adding URLs for each of the 23 services included in the study. Other suggestions include explaining why overlay journals were excluded, clarifying the limitation related to including only English-language platforms, archiving rawer input data to improve reproducibility, adding details related to the qualitative text analysis, discussing any existing empirical evidence about misconduct as it relates to different models of peer review, and improving field inclusiveness by avoiding conflation of “research” and “scientific research.”
The reviewers and I agree that the article is a valuable contribution to the metaresearch literature related to peer review processes.
Peer Review 1
Thank you very much for the opportunity to review the preprint titled “Preprint review services: Disrupting the scholarly communication landscape?” (https://doi.org/10.31235/osf.io/8c6xm) The authors review services that facilitate peer review of preprints, primarily in the STEM (science, technology, engineering, and math) disciplines. They examine how these services operate and their role within the scholarly publishing ecosystem. Additionally, the authors discuss the potential benefits of these preprint peer review services, placing them in the context of tensions in the broader peer review reform movement. The discussions are organized according to four “schools of thought” in peer review reform, as outlined by Waltman et al. (2023), which provides a useful framework for analyzing the services. In terms of methodology, I believe the authors were thorough in their search for preprint review services, especially given that a systematic search might be impractical.
As I see it, the adoption of preprints and reforming peer review are key components of the move towards improving scholarly communication and open research. This article is a useful step along that journey, taking stock of current progress, with a discussion that illuminates possible paths forward. It is also well-structured and easy for me to follow. I believe it is a valuable contribution to the metaresearch literature.
On a high level, I believe the authors have made a reasonable case that preprint review services might make peer review more transparent and rewarding for all involved. Looking forward, I would like to see metaresearch which gathers further evidence that these benefits are truly being realised.
In this review, I will present some general points which merit further discussion or clarification to aid an uninitiated reader. Additionally, I raise one issue regarding how the authors framed the article and categorised preprint review services and the disciplines they serve. In my view, this problem does not fundamentally undermine the robust search, analyses, and discussion in this paper, but it risks putting off some researchers and constrains how broadly one should derive conclusions.
General comments
Some metaresearchers may be aware of preprints, but not all readers will be familiar with them. I suggest briefly defining what they are, how they work, and which types of research have benefited from preprints, similar to how “preprint review service” is clearly defined in the introduction.
Regarding Waltman et al.’s (2023) “Equity & Inclusion” school of thought, does it specifically aim for “balanced” representation by different groups as stated in this article? There is an important difference between “balanced” versus “equitable” representation, and I would like to see it addressed in this text.
Another analysis I would like to see is whether any of the 23 services reviewed present any evidence that their approach has improved research quality. For instance, the discussion on peer review efficiency and incentives states that there is currently “no hard evidence” that journals want to utilise reviews by Rapid Reviews: COVID-19, and that “not all journals are receptive” to partnerships. Are journals skeptical of whether preprint review services could improve research quality? Or might another dynamic be at work?
The authors cite Nguyen et al. (2015) and Okuzaki et al. (2019), stating that peer review is often “overloaded”. I would like to see a clearer explanation by what “overloaded” means in this context so that a reader does not have to read the two cited papers.
To the best of my understanding, one of the major sticking points in peer review reform is whether to anonymise reviewers and/or authors. Consequently, I appreciate the comprehensive discussion about this issue by the authors.
However, I am only partially convinced by the statement that double anonymity is “essentially incompatible” with preprint review. For example, there may be, as yet not fully explored, ways to publish anonymous preprints with (a) a notice that it has been submitted to, or is undergoing, peer review; and (b) that the authors will be revealed once peer review has been performed (e.g. at least one review has been published). This would avoid the issue of publishing only after review is concluded as is the case for Hypothesis and Peer Community In.
Additionally, the authors describe 13 services which aim to “balance transparency and protect reviewers’ interests”. This is a laudable goal, but I am concerned that framing this as a “balance” implies a binary choice, and that to have more of one, we must lose an equal amount of the other. Thinking only in terms of “balance” prevents creative, win-win solutions. Could a case be made for non-anonymity to be complemented by a reputation system for authors and reviewers? For example, major misconduct (e.g. retribution against a critical review) would be recorded in that system and dissuade bad actors. Something similar can already be seen in the reviewer evaluation system of CrowdPeer, which could plausibly be extended or modified to highlight misconduct.
I also note that misconduct and abusive behaviour already occur even in fully or partially anonymised peer review, and they are not limited to the review or preprints. While I am not aware of existing literature on this topic, academics’ fears seem reasonable. For example, there is at least anecdotal testimonies that a reviewer would deliberately reject a paper to retard the progress of a rival research group, while taking the ideas of that paper and beating their competitors to winning a grant. Or, a junior researcher might refrain from giving a negative review out of fear that the senior researcher whose work they are reviewing might retaliate. These fears, real or not, seem to play a part in the debates about if and how peer review should (or should not) be anonymised. I would like to see an exploration of whether de-anonimisation will improve or worsen this behaviour and in what contexts. And if such studies exist, it would be good to discuss them in this paper.
I found it interesting that almost all preprint review services claim to be complementary to, and not compete with, traditional journal-based peer review. The methodology described in this article cannot definitely explain what is going on, but I suspect there may be a connection between this aversion to compete with traditional journals, and (a) the skepticism of journals towards partnering with preprint review services and (b) the dearth of publisher-run options. I hypothesise that there is a power dynamic at play, where traditional publishers have a vested interest in maintaining the power they hold over scholarly communication, and that preprint review services stress their complementarity (instead of competitiveness) as a survival mechanism. This may be an avenue for further metaresearch.
To understand preprints from which fields of research are actually present on the services categorised under “all disciplines,” I used the Random Integer Set Generator by the Random.org true random number service (https://www.random.org/integer-sets/) to select five services for closer examination: Hypothesis, Peeriodicals, PubPeer, Qeios, and Researchers One. Of those, I observed that Hypothesis is an open source web annotation service that allows commenting on and discussion of any web page on the Internet regardless of whether it is research or preprints. Hypothesis has a sub-project named TRiP (Transparent Review in Preprints), which is their preprint review service in collaboration with Cold Spring Harbor Laboratory. It is unclear to me why the authors listed Hypothesis as the service name in Table 1 (and elsewhere) instead of TRiP (or other similar sub-projects). In addition, Hypothesis seems to be framed as a generic web annotation service that is used by some as a preprint review tool. This seems fundamentally different from others who are explicitly set up as preprint review services. This difference seems noteworthy to me.
To aid readers, I also suggest including hyperlinks to the 23 services reviewed in this paper. My comments on disciplinary representation in these services are elaborated further below.
One minor point of curiosity is that several services use an “automated tool” to select reviewers. It would be helpful to describe in this paper exactly what those tools are and how they work, or report situations where services do not explain it.
Lastly, what did the authors mean by “software heritage” in section 6? Are they referring to the organisation named Software Heritage (https://www.softwareheritage.org/) or something else? It is not clear to me how preprint reviews would be deposited in this context.
Respecting disciplinary and epistemic diversity
In the abstract and elsewhere in the article, the authors acknowledge that preprints are gaining momentum “in some fields” as a way to share “scientific” findings. After reading this article, I agree that preprint review services may disrupt publishing for research communities where preprints are in the process of being adopted or already normalised. However, I am less convinced that such disruption is occurring, or could occur, for scholarly publishing more generally.
I am particularly concerned about the casual conflation of “research” and “scientific research” in this article. Right from the start, it mentions how preprints allow sharing “new scientific findings” in the abstract, stating they “make scientific work available rapidly.” It also notes that preprints enable “scientific work to be accessed in a timely way not only by scientists, but also…” This framing implies that all “scholarly communication,” as mentioned in the title, is synonymous with “scientific communication.” Such language excludes researchers who do not typically identify their work as “scientific” research. Another example of this conflation appears in the caption for Figure 1, which outlines potential benefits of preprint review services. Here, “users” are defined as “scientists, policymakers, journalists, and citizens in general.” But what about researchers and scholars who do not see themselves as “scientists”?
Similarly, the authors describe the 23 preprint review services using six categories, one of which is “scientific discipline”. One of those disciplines is called “humanities” in the text, and Table 1 lists it as a discipline for Science Open Reviewed. Do the authors consider “humanities” to be a “scientific” discipline? If so, I think that needs to be justified with very strong evidence.
Additionally, Waltman et al.’s four schools of thought for peer review reform works well with the 23 services analysed. However, at least three out of the four are explicitly described as improving “scientific” research.
Related to the above are how the five “scientific disciplines” are described as the “usual organisation” of the scholarly communication landscape. On what basis should they be considered “usual”? In this formulation, research in literature, history, music, philosophy, and many other subjects would all be lumped together into the “humanities”, which sit at the same hierarchical level as “biomedical and life sciences”, arguably a much more specific discipline. My point is not to argue for a specific organisation of research disciplines, but to highlight a key epistemic assumption underlying the whole paper that comes across as very STEM-centric (science, technology, engineering, and math).
How might this part of the methodology affect the categories presented in Table 1? “Biomedical and life sciences” appear to be overrepresented compared to other “disciplines”. I’d like to see a discussion that examines this pattern, and considers why preprint review services (or maybe even preprints more generally) appear to cover mostly the biomedical or physical sciences.
In addition, there are 12 services described as serving “all disciplines”. I believe this paper can be improved by at least a qualitative assessment of the diversity of disciplines actually represented on those services. Because it is reported that many of these service stress improving the “reproducibility” of research, I suspect most of them serve disciplines which rely on experimental science.
I randomly selected five services for closer examination, as mentioned above. Of those, only Qeios has demonstrated an attempt to at least split “arts and humanities” into subfields. The others either don’t have such categories altogether, or have a clear focus on a few disciplines (e.g. life sciences for Hypothesis/TRiP). In all cases I studied, there is a heavy focus on STEM subjects, especially biology or medical research. However, they are all categorised by the authors as serving “all disciplines”.
If preprint review services originate from, or mostly serve, a narrow range of STEM disciplines (especially experiment-based ones), it would be worth examining why that is the case, and whether preprints and reviews of them could (or could not) serve other disciplines and epistemologies.
It is postulated that preprint review services might “disrupt the scholarly communication landscape in a more radical way”. Considering the problematic language I observed, what about fields of research where peer-reviewed journal publications are not the primary form of communication? Would preprint review services disrupt their scholarly communications?
To be clear, my concern is not just the conflation of language in a linguistic sense but rather inequitable epistemic power. I worry that this conflation would (a) exclude, minoritise, and alienate researchers of diverse disciplines from engaging with metaresearch; and (b) blind us from a clear pattern in these 23 services, that is their strong focus on the life sciences and medical research and a discussion of why that might be the case. Critically, what message are we sending to, for example, a researcher of 18th century French poetry with the language and framing of this paper? I believe the way “disciplines” are currently presented here poses a real risk of devaluing and minoritising certain subject areas and ways of knowing. In its current form, I believe that while this paper is a very valuable contribution, one should not derive from it any conclusions which apply to scholarly publishing as a whole.
The authors have demonstrated inclusive language elsewhere. For example, they have consciously avoided “peer” when discussing preprint review services, clearly contrasting them to “journal-based peer review”. Therefore, I respectfully suggest that similar sensitivity be adopted to avoid treating “scientific research” and “research” as the same thing. A discussion, or reference to existing works, on the disciplinary skew of preprints (and reviews of them) would also add to the intellectual rigour of this already excellent piece.
Overall, I believe this paper is a valuable reflection on the state of preprints and services which review them. Addressing the points I raised, especially the use of more inclusive language with regards to disciplinary diversity, would further elevate its usefulness in the metaresearch discourse. Thank you again for the chance to review.
Signed:
Dr Pen-Yuan Hsing (ORCID ID: 0000-0002-5394-879X)
University of Bristol, United Kingdom
Data availability
I have checked the associated dataset, but still suggest including hyperlinks to the 23 services analysed in the main text of this paper.
Peer Review 2
This manuscript examines preprint review services and their role in the scholarly communications ecosystem. It seems quite thorough to me. In Table 1 they list many peer-review services that I was unaware of e.g. SciRate and Sinai Immunology Review Project.
To help elicit critical & confirmatory responses for this peer review report I am trialling Elsevier’s suggested “structured peer review” core questions, and treating this manuscript as a research article.
Introduction
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Is the background and literature section up to date and appropriate for the topic?
Yes.
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Are the primary (and secondary) objectives clearly stated at the end of the introduction?
No. Instead the authors have chosen to put the two research questions on page 6 in the methods section. I wonder if they ought to be moved into the introduction – the research questions are not methods in themselves. Might it be better to state the research questions first and then detail the methods one uses to address those questions afterwards? [as Elsevier’s structured template seems implicitly to prefer.
Methods
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Are the study methods (including theory/applicability/modelling) reported in sufficient detail to allow for their replicability or reproducibility?
I note with approval that the version number of the software they used (ATLAS.ti) was given.
I note with approval that the underlying data is publicly archived under CC BY at figshare.
The Atlas.ti report data spreadsheet could do with some small improvement – the column headers are little cryptic e.g. “Nº ST “ and “ST” which I eventually deduced was Number of Schools of Thought and Schools of Thought (?)
Is there a rawer form of the data that could be deposited with which to evidence the work done? The Atlas.ti report spreadsheet seemed like it was downstream output data from Atlas.ti. What was the rawer input data entered into Atlas.ti? Can this be archived somewhere in case researchers want to reanalyse it using other tools and methods.
I note with disapproval that Atlas.ti is proprietary software which may hinder the reproducibility of this work. Nonetheless I acknowledge that Atlas.ti usage is somewhat ‘accepted’ in social sciences despite this issue.
I think the qualitative text analysis is a little vague and/or under-described: “Using ATLAS.ti Windows (version 23.0.8.0), we carried out a qualitative analysis of text from the relevant sites, assigning codes covering what they do and why they have chosen to do it that way.” That’s not enough detail. Perhaps an example or two could be given? Was inter-rater reliability performed when ‘assigning codes’ ? How do we know the ‘codes’ were assigned accurately?
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Are statistical analyses, controls, sampling mechanism, and statistical reporting (e.g., P-values, CIs, effect sizes) appropriate and well described?
This is a descriptive study (and that’s fine) so there aren’t really any statistics on show here other than simple ‘counts’ (of Schools of Thought) in this manuscript. There are probably some statistical processes going on within the proprietary qualitative analysis of text done in ATLAS.ti but it is under described and so hard for me to evaluate.
Results
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Is the results presentation, including the number of tables and figures, appropriate to best present the study findings?
Yes. However, I think a canonical URL to each service should be given. A URL is very useful for disambiguation, to confirm e.g. that the authors mean this Hypothesis (www.hypothes.is) and NOT this Hypothesis (www.hyp.io). I know exactly which Hypothesis is the one the authors are referring to but we cannot assume all readers are experts 😊
Optional suggestion: I wonder if the authors couldn’t present the table data in a slightly more visual and/or compact way? It’s not very visually appealing in its current state. Purely as an optional suggestion, to make the table more compact one could recode the answers given in one or more of the columns 2, 3 and 4 in the table e.g. “all disciplines = ⬤ , biomedical and life sciences = ▲, social sciences = ‡ , engineering and technology = † “. I note this would give more space in the table to print the URLs for each service that both reviewers have requested.
Service name Developed by Scientific disciplines Types of outputs Episciences Other ⬤ blah blah blah. Faculty Opinions Individual researcher ▲ blah blah blah. Red Team Market Individual researcher ‡ blah blah blah. The “Types of outputs” column might even lend themselves to mini-colour-pictograms (?) which could be more concise and more visually appealing? A table just of text, might be scientifically ‘correct’ but it is incredibly dull for readers, in my opinion.
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Are additional sub-analyses or statistical measures needed (e.g., reporting of CIs, effect sizes, sensitivity analyses)?
No / Not applicable.
Discussion
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Is the interpretation of results and study conclusions supported by the data and the study design?
Yes.
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Have the authors clearly emphasized the limitations of their study/theory/methods/argument?
No. Perhaps a discussion of the linguistic/comprehension bias of the authors might be appropriate for this manuscript. What if there are ‘local’ or regional Chinese, Japanese, Indonesian or Arabic language preprint review services out there? Would this authorship team really be able to find them?
Additional points:
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Perhaps the points made in this manuscript about financial sustainability (p24) are a little too pessimistic. I get it, there is merit to this argument, but there is also some significant investment going on there if you know where to look. Perhaps it might be worth citing some recent investments e.g. Gates -> PREreview (2024) https://content.prereview.org/prereview-welcomes-funding/ and Arcadia’s $4 million USD to COAR for the Notify Project which supports a range of preprint review communities including Peer Community In, Episciences, PREreview and Harvard Library. (source: https://coar-repositories.org/news-updates/coar-welcomes-significant-funding-for-the-notify-project/ )
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Although I note they are mentioned, I think more needs to be written about the similarity and overlap between ‘overlay journals’ and preprint review services. Are these arguably not just two different terms for kinda the same thing? If you have Peer Community In which has it’s overlay component in the form of the Peer Community Journal, why not mention other overlay journals like Discrete Analysis and The Open Journal of Astrophysics. I think Peer Community In (& it’s PCJ) is the go-to example of the thin-ness of the line the separates (or doesn’t!) overlay journals and preprint review services. Some more exposition on this would be useful.
Author Response
We would like to sincerely thank the editor and the two reviewers for their meticulous evaluation and constructive feedback. Their thoughtful comments and insightful suggestions have been invaluable in enhancing the clarity, and strengthening the overall quality of the manuscript. We are truly grateful for the time and expertise they have devoted to improving this work.
In the revised version of the manuscript, we have therefore improved its structure, clarified the study’s focus, and enhanced the clarity of its presentation.
We hope that the revised version more effectively articulates the motivation and design of the study and that our detailed responses below comprehensively address the constructive and thoughtful feedback from each reviewer.
Response to Reviewer 1 (Pen-Yuan Hsing)
[General comments]
We sincerely thank the reviewer for their thoughtful feedback, as well as for the valuable suggestions to improve the manuscript’s structure. The comments were highly constructive and helped improve the study’s focus and the clarity of its presentation.
Reviewer comment:
“Some metaresearchers may be aware of preprints, but not all readers will be familiar with them. I suggest briefly defining what they are, how they work, and which types of research have benefited from preprints, similar to how “preprint review service” is clearly defined in the introduction.”
Following the reviewer’s suggestion, we have expanded the Introduction section to briefly define preprints, explain how they work, and indicate which types of research have benefited from them.
Reviewer comment:
“Regarding Waltman et al.’s (2023) “Equity & Inclusion” school of thought, does it specifically aim for “balanced” representation by different groups as stated in this article? There is an important difference between “balanced” versus “equitable” representation, and I would like to see it addressed in this text.”
According to Waltman et al. (2023), the “Equity & Inclusion” school of thought “promotes a balanced representation of different groups of researchers in the peer review system (in particular in gatekeeping roles as editor or reviewer) in order to create a more diverse and inclusive research system as a whole.” For this reason, we referred to the aim of achieving “balanced” representation across different groups.
Reviewer comment:
“Another analysis I would like to see is whether any of the 23 services reviewed present any evidence that their approach has improved research quality. For instance, the discussion on peer review efficiency and incentives states that there is currently “no hard evidence” that journals want to utilise reviews by Rapid Reviews: COVID-19, and that “not all journals are receptive” to partnerships. Are journals skeptical of whether preprint review services could improve research quality? Or might another dynamic be at work?”
Unfortunately, based on the information available in ReimagineReview and in the supplementary sources we consulted (e.g., service websites, blog posts, and scientific articles), it was not possible to present evidence on whether the work of the analyzed preprint review services has improved research quality. Nevertheless, we recognize the importance of this issue and intend to examine it in greater depth in a follow-up study currently in development.
Reviewer comment:
“The authors cite Nguyen et al. (2015) and Okuzaki et al. (2019), stating that peer review is often “overloaded”. I would like to see a clearer explanation by what “overloaded” means in this context so that a reader does not have to read the two cited papers.”
To clarify the concept of “overloaded” as used by Nguyen et al. (2015) and Okuzaki et al. (2019), we have expanded our explanation in the revised manuscript, making clear that “overloaded” refers to excessive review times and the growing burden on reviewers and editors contributing to substantial delays in publication.
Reviewer comment:
“To the best of my understanding, one of the major sticking points in peer review reform is whether to anonymise reviewers and/or authors. Consequently, I appreciate the comprehensive discussion about this issue by the authors.
However, I am only partially convinced by the statement that double anonymity is “essentially incompatible” with preprint review.
Our view that double anonymity is “essentially incompatible” with preprint review is based on the fact that preprinting is explicitly intended to promote transparency by making research outputs, including the names of the authors, openly accessible at an early stage and fostering open discussion involving named authors, whereas double-anonymous peer review relies on protecting author and reviewer identities and therefore, while potentially more inclusive, tends to be less transparent and incompatible with early sharing of research results. When authors share their research results at an early stage by preprinting their work, reviewers can always look up the preprinted work and see the identities of the authors, which means peer review cannot be truly double-anonymous. For this reason, we have highlighted in the manuscript the efforts of some of the analyzed services to “manage the tensions between the drive for transparency, characteristic of preprinting, and the pursuit of inclusiveness”.
Reviewer comment:
“I would like to see an exploration of whether de-anonimisation will improve or worsen this behaviour and in what contexts. And if such studies exist, it would be good to discuss them in this paper.”
We agree it is important to explore whether de-anonimisation will improve or worsen misconduct and abusive behaviour and in what contexts. Given the descriptive nature of our work, we are unable to address this issue in more depth within the current manuscript. However, we intend to examine the issue in greater depth in a follow-up study currently in development.
Reviewer comment:
“I found it interesting that almost all preprint review services claim to be complementary to, and not compete with, traditional journal-based peer review. The methodology described in this article cannot definitely explain what is going on, but I suspect there may be a connection between this aversion to compete with traditional journals, and (a) the skepticism of journals towards partnering with preprint review services and (b) the dearth of publisher-run options. I hypothesise that there is a power dynamic at play, where traditional publishers have a vested interest in maintaining the power they hold over scholarly communication, and that preprint review services stress their complementarity as a survival mechanism. This may be an avenue for further metaresearch.”
We agree that this is an interesting feature of the data. Given the descriptive nature of our work, it is not possible in this study to explain why almost all preprint review services claim to be complementary to, and not compete with, traditional journal-based peer review. We recognize the importance of this issue and intend to further develop this discussion in future work.
Reviewer comment:
“To aid readers, I also suggest including hyperlinks to the 23 services reviewed in this paper.”
We fully agree that providing URLs would be valuable for disambiguation. However, by the time we finalized our manuscript, some URLs were no longer available, and some services have since evolved into different things, as noted in the Methods section of the manuscript:
“The websites of two preprint review services included in our initial set became unavailable after November 2022.”
“On the other hand, some services have evolved… This is the case for Rapid Reviews: COVID-19, which has expanded beyond COVID-19.”
Although we acknowledge the inherent risk of URLs becoming outdated, we decided to include them in the manuscript in accordance with the reviewer’s suggestion (see Table 1). The revised version of Table 1 is also available on Figshare.
Reviewer comment:
“One minor point of curiosity is that several services use an “automated tool” to select reviewers. It would be helpful to describe in this paper exactly what those tools are and how they work, or report situations where services do not explain it.”
Given the descriptive nature of our work, we are unable to address this issue in more depth within the current manuscript. However, we intend to examine the issue in greater depth in a follow-up study currently in development.
Reviewer comment:
“Lastly, what did the authors mean by “software heritage” in section 6? Are they referring to the organisation named Software Heritage (https://www.softwareheritage.org/) or something else? It is not clear to me how preprint reviews would be deposited in this context.”
We confirm that we were referring to the organization Software Heritage (https://www.softwareheritage.org/). On reflection, however, we have decided to delete the text referring to Software Heritage.
[Respecting disciplinary and epistemic diversity]
We appreciate the reviewer’s thoughtful questions regarding the following terminological issues. Detailed responses to each of the points raised are provided below.
“research” and “scientific research” – to ensure consistency, we have standardized the terminology by using the term “research” throughout, and the expression “scientific research” no longer appears in the manuscript.
“users” in the caption for Figure 1 – the term “users” is intended as a broad designation, without any intention of excluding anyone. Nevertheless, following the reviewer’s suggestion, to improve clarity and maintain consistency throughout the manuscript, we have opted to use the term “researchers” as a general designation encompassing scientists, scholars, and others engaged in research activities. We believe this single inclusive term offers the intended breadth of reference.
“scientific disciplines” – in the manuscript, the five broad areas – Physical Sciences, Biomedical and Life Sciences, Engineering and Technology, Social Sciences, and Humanities – are described as the “usual organization” of the scholarly communication landscape because they reflect a widely recognized, high-level disciplinary structure used by international organizations and classification systems. Although there are other alternative disciplinary taxonomies, this five-fold division provides a commonly accepted point of reference for analyzing and comparing developments across the scholarly communication system.
“all disciplines” – as mentioned in the manuscript, we used the category “All Disciplines” to designate services that host work from any scientific field or that adopt a multidisciplinary approach without clearly defining the disciplines or sub-disciplines included. Our qualitative analysis relied on the information available in ReimagineReview, supplemented with desk research using online sources such as the websites of preprint review services, blog posts, and scientific articles. Unlike the reviewer’s own closer examination of a subset of services, we did not undertake this level of detailed assessment within the scope of the present study. Nevertheless, we recognize the need for further clarification and intend to explore this issue in greater depth in a follow-up study currently in development.
Response to Reviewer 2 (Ross Mounce)
We sincerely thank the reviewer for their thoughtful feedback, as well as for the valuable suggestions to improve the manuscript’s structure. The comments were highly constructive and helped improve the study’s focus and the clarity of its presentation.
Reviewer comment:
“…the authors have chosen to put the two research questions on page 6 in the methods section. I wonder if they ought to be moved into the introduction – the research questions are not methods in themselves. Might it be better to state the research questions first and then detail the methods one uses to address those questions afterwards?”
We agree that presenting the research questions in the introduction provides a clearer structure and better context for the study. Accordingly, we have moved the research questions from the Methods section to the Introduction section. In addition, we now also refer explicitly to the research questions in the Conclusions section.
Reviewer comment:
“The Atlas.ti report data spreadsheet could do with some small improvement – the column headers are little cryptic e.g. “Nº ST “ and “ST” which I eventually deduced was Number of Schools of Thought and Schools of Thought (?)”
With regard to the Atlas.ti report data spreadsheet available at figshare, we agree that the column headers were a little cryptic and so a new version of the table (Atlas.ti_Report_Preprint_Review_Services_vs_Schools_V2) is now available in figshare, with the headers: “Number of Schools of Thought” and “Schools of Thought” (instead of “Nº ST “ and “ST”).
Reviewer comment:
“Is there a rawer form of the data that could be deposited with which to evidence the work done? The Atlas.ti report spreadsheet seemed like it was downstream output data from Atlas.ti. What was the rawer input data entered into Atlas.ti? Can this be archived somewhere in case researchers want to reanalyse it using other tools and methods.”
We fully agree on the importance of ensuring open access to the raw input data analyzed in Atlas.ti, so that other researchers may reanalyze it using different tools and methods. For this reason, the complete set of raw input data for each service has been made openly available on Figshare as Word documents (e.g., Hypothesis.docx, Peer Community in.docx).
Reviewer comment:
“I think the qualitative text analysis is a little vague and/or under-described: “Using ATLAS.ti Windows (version 23.0.8.0), we carried out a qualitative analysis of text from the relevant sites, assigning codes covering what they do and why they have chosen to do it that way.” That’s not enough detail. Perhaps an example or two could be given? Was inter-rater reliability performed when ‘assigning codes’ ? How do we know the ‘codes’ were assigned accurately?”
We agree that the description of the qualitative text analysis could be more detailed, and so we have added some additional information in the Methods section. It should be noted for clarification that we did not conduct a formal inter-rater reliability assessment. Instead, to ensure accuracy in the coding process, one of the authors (SOH) first applied the coding scheme to the dataset. To ensure accuracy in the coding process, codes were then refined and validated through group discussion with the other authors, and consensus was reached regarding any changes, thereby ensuring consistency. Where there was ambiguity in project descriptions, we contacted the service managers to clarify and confirm some details. As noted in the manuscript, the four peer review schools of thought were originally proposed by some of us (Waltman et al., 2023), which enabled us to apply the framework with greater confidence when evaluating the characteristics of the 23 preprint review services against the key issues raised by these schools.
Reviewer comment:
“This is a descriptive study (and that’s fine) so there aren’t really any statistics on show here other than simple ‘counts’ (of Schools of Thought) in this manuscript. There are probably some statistical processes going on within the proprietary qualitative analysis of text done in ATLAS.ti but it is under-described and so hard for me to evaluate.”
As the reviewer correctly noted, this is a descriptive study, and no statistical analyses were performed using ATLAS.ti.
Reviewer comment:
“I think a canonical URL to each service should be given. A URL is very useful for disambiguation, to confirm e.g. that the authors mean this Hypothesis DONE (www.hypothes.is) and NOT this Hypothesis (www.hyp.io). I know exactly which Hypothesis is the one the authors are referring to but we cannot assume all readers are experts.”
We fully agree that providing URLs would be valuable for disambiguation. However, by the time we finalized our manuscript, some URLs were no longer available, and some services have since evolved into different things, as noted in the Methods section:
“The websites of two preprint review services included in our initial set became unavailable after November 2022.”
“On the other hand, some services have evolved… This is the case for Rapid Reviews: COVID-19, which has expanded beyond COVID-19.”
While acknowledging the inherent risk of URLs becoming outdated, we have included URLs in the revised manuscript in accordance with the reviewer’s suggestion (see Table 1). The revised version of Table 1 is also available on Figshare.
Reviewer comment:
“I wonder if the authors couldn’t present the table data in a slightly more visual and/or compact way? It’s not very visually appealing in its current state. Purely as an optional suggestion, to make the table more compact one could recode the answers given in one or more of the columns 2, 3 and 4 in the table e.g. “all disciplines = ⬤ , biomedical and life sciences = ▲, social sciences = ‡ , engineering and technology = † “. I note this would give more space in the table to print the URLs for each service that both reviewers have requested.”
After exploring several visual approaches, to present the table data in a more visual and/or compact format, we found that maintaining the current text-based format provides clearer information and facilitates better understanding. While it may be less visually appealing, we believe this format conveys the data more effectively and comprehensively.
Reviewer comment:
“Perhaps a discussion of the linguistic/comprehension bias of the authors might be appropriate for this manuscript. What if there are ‘local’ or regional Chinese, Japanese, Indonesian or Arabic language preprint review services out there? Would this authorship team really be able to find them?”
In the revised manuscript, we explicitly acknowledge this issue in the Methods section:
“For pragmatic reasons, we focus exclusively on English-language services, so services that may exist in other languages are not included in our study.”
Reviewer comment:
“Perhaps the points made in this manuscript about financial sustainability (p24) are a little too pessimistic. I get it, there is merit to this argument, but there is also some significant investment going on there if you know where to look. Perhaps it might be worth citing some recent investments e.g. Gates -> PREreview (2024) https://content.prereview.org/prereview-welcomes-funding/ and Arcadia’s $4 million USD to COAR for the Notify Project which supports a range of preprint review communities including Peer Community In, Episciences, PREreview and Harvard Library. (source: https://coar-repositories.org/news-updates/coar-welcomes-significant-funding-for-the-notify-project/ )”
We thank the reviewer for this valuable observation and for pointing out recent examples of significant investment in the field. We agree that our discussion of sustainability may appear somewhat pessimistic. Within our sample of 23 preprint review services, however, we observed considerable variation in organizational models, structures, teams, budgets, and services offered. While some initiatives, such as those highlighted by the reviewer, are growing and benefiting from promising funding opportunities, others continue to struggle with sustainability. Overall, we therefore consider sustainability to remain one of the key challenges facing these services. We also recognize the importance of this issue and plan to explore it in greater depth in a follow-up study currently in development.
Reviewer comment:
“Although I note they are mentioned, I think more needs to be written about the similarity and overlap between ‘overlay journals’ and preprint review services. Are these arguably not just two different terms for kinda the same thing? If you have Peer Community In which has it’s overlay component in the form of the Peer Community Journal, why not mention other overlay journals like Discrete Analysis and The Open Journal of Astrophysics. I think Peer Community In (& it’s PCJ) is the go-to example of the thin-ness of the line the separates (or doesn’t!) overlay journals and preprint review services. Some more exposition on this would be useful.”
Regarding the overlap between overlay journals and preprint review services, we agree that the distinction is often thin. While our manuscript focuses on preprint review services, we now explicitly acknowledge in the Introduction section that the distinction between preprint review services and overlay journals is often thin, with examples such as Peer Community In (and its Peer Community Journal), and Rapid Reviews: Infectious Diseases (formerly known as Rapid Reviews: COVID-19) illustrating their close overlap.



