Editorial Policies
Correction, Retraction, and Removal of Articles
Corresponding Author Responsibilities
Artificial Intelligence Generated Content (AIGC)
Peer Review Process
JLSC uses a double anonymous review process for peer-reviewed submissions, meaning the authors' and reviewers' identities are not revealed to each other during review.
For articles where it would be difficult to fully anonymize the author, we allow authors to opt into a semi-anonymous review, where the author's affiliation is not anonymized in the manuscript. In no case is the author's name shared with the reviewers. Published articles will indicate which type of review the article underwent (semi- or fully anonymous).
The editor(s) will perform an initial review of all submitted manuscripts and may reject papers that are clearly outside of the scope of the journal. Manuscripts within the scope will be sent to at least two reviewers. Reviewers will not receive or be able to view any documentation or metadata that includes individually identifiable author information. Authors will be provided with similarly anonymized reviewer comments to aid in the revision of their manuscripts.
The review process takes, on average, eight weeks. Authors may not submit the manuscript to other publications while a review is in progress.
All articles will undergo peer review following section guidelines, regardless of contact prior to submission.
Peer Reviewers
JLSC strives to select reviewers from diverse identities, backgrounds, geographic areas, and career levels. Editors primarily draw upon those who have registered as reviewers on the JLSC site and have clearly articulated reviewing interests, although external reviewers will be sought when needed. Selection is based on reviewer expertise on the manuscript topic, through practice and/or scholarship.
In an initial query, reviewers will be provided the article title and abstract and a due date for the article. (Potential reviewers who are interested in reviewing but unable to make the proposed due date are encouraged to discuss an adjusted date with the JLSC editor; extensions can typically be granted, within reason.) Upon acceptance, reviewers will be provided with access to an anonymized manuscript and a form on the JLSC site with questions to guide their feedback. Reviewers will also be asked to provide a general recommendation for the manuscript (e.g. accept, revisions required, declined). Reviews will be shared with authors anonymously and retained on the JLSC system, although reviewers will retain copyright of any comments submitted. Reviewers are uncompensated, but editors will provide letters of acknowledgment and thanks for potential inclusion in annual review documentation.
The JLSC editorial team encourages those with experience in any of the topics listed in the Focus and Scope and interested in reviewing to:
- Sign up using the “Become a Reviewer” button.
- Please make sure to clearly articulate your reviewing interests.
- Reviewers need not have reviewed previously or have a publication history.
- Early career professionals are welcome.
Copyediting
JLSC provides professional copyediting to all accepted manuscripts. Nevertheless, authors are expected to proofread manuscripts to minimize typographical and grammatical errors, and may be requested to perform additional editing on their manuscripts if it is deemed necessary. If a submission exhibits potential but requires extensive stylistic revision, the editors may strongly encourage authors to employ a colleague or professional reader to review the manuscript.
Correction, Retraction, and Removal of Articles
Correction
Despite the best of efforts, errors occur and their timely and effective remedy are considered the mark of responsible authors and editors. JLSC will publish a correction if the scholarly record is seriously affected (e.g., if accuracy/intended meaning, scientific reproducibility, author reputation, or journal reputation is judged to be compromised). Corrections that do not affect the contribution in a material way or significantly alter the reader's understanding of the contribution, such as misspellings or grammatical errors, will not be published. When a correction is published, it will link to and from the work. The correction will be added to the original work so that readers will receive the original work and the correction. All corrections will be as concise as possible.
Retraction
JLSC reserves the right to retract items, with a retraction defined as a public disavowal, not an erasure or removal. Retractions will occur if the editors and editorial board finds that the main conclusion of the work is undermined or if subsequent information about the work comes to light of which the authors or the editors were not aware at the time of publication. Infringements of professional ethical codes, such as multiple submission, inaccurate claims of authorship, plagiarism, fraudulent use of data will also result in retraction of the work.
Removal
Some circumstances may necessitate removal of a work from JLSC. This will occur when the article is judged by the editors and editorial board to be defamatory, if it infringes on legal rights, or if there is a reasonable expectation that it will be subject to a court order. The bibliographic information about the work will be retained online, but the work will no longer be available through JLSC. A note will be added to indicate that the item was removed for legal reasons.
Name and Pronoun Changes
As part of our commitment to authors and the research community, JLSC has introduced a policy to enable name and pronoun changes for our authors. Going forward, all requests to make a name or pronoun change will be honored. This includes, but is not limited to, name changes because of marriage, divorce, gender affirmation, and religious conversion. JLSC will not require any form of proof or supporting documentation beyond what is needed to confirm the author’s identity and will only note that a non-substantive change was made to the published article.
JLSC can only make changes to the article (including all of its formats on the JLSC website) and journal webpage (i.e., where the DOI resolves). JLSC cannot control updates in indexes/databases that have picked up the original metadata, and we are unable to update citations to articles in which a name change has occurred. JLSC will not notify co-authors of the change to the article; authors may choose whether or not they wish to alert their co-authors.
Any misuse of this policy will be considered misconduct, and JLSC reserves the right to investigate and act against misuse.
How to request a name change
Authors who wish to change their name on any work previously published in JLSC are asked to fill out this form.
Corresponding Author Responsibilities
The corresponding author must submit the manuscript and related files (e.g. supporting data files, media, etc.). From the point of submission through to publication, all communication related to that manuscript will be directed to and received from the corresponding author. It is the responsibility of the corresponding author to ensure that all authors are aware of and approve the submission of the manuscript, its content, authorship, and order of authorship. Confirmation of this action is required at submission of all manuscripts.
For more information on JLSC’s authorship guidelines, please review our Criteria for Authorship.
Masking Manuscripts Prior to Submission
The corresponding author is responsible for ensuring the submitted manuscript has been appropriately prepared for anonymous review. No individually identifiable information/references to the author(s) should be included in the manuscript (or title page). Acknowledgments should not be included in the manuscript; they may be entered separately during the submission process.
In addition to removing all individually identifiable information from within the document, the corresponding author should check the document properties and remove any identifiable information.
All supplemental files (figures, images, data sets, etc.) should also have any individually identifiable information removed prior to submission.
If the authors wish to submit a cover letter with the manuscript, it may contain identifiable information, and will be submitted/uploaded separate from the manuscript file to preserve the anonymous review process.
Data Sharing
For the purposes of this policy, the term "data" is understood broadly and refers to both quantitative and qualitative research outputs, spanning observations and analysis of social settings (producing numbers, texts, images, multimedia or other content) to numbers attained through instrumental and other raw data gathering efforts, quantitative analysis, text mining, or citation analysis, as well as protocols, methods, and code used to generate any specific finding reported in the paper.
Authors of research papers submitted for publication in JLSC are encouraged, whenever possible, to make the data underlying their manuscripts available online prior to submission, preferably in a secure, public repository that provides a persistent identifier, assures long-term access, and provides sufficient documentation and metadata to support re-use by others (e.g., institutional repository, data repository, Zenodo). In any case, a citation to the dataset should be made in the manuscript itself in accordance with the data citation principles of the FORCE11 Joint Declaration of Data Citation Principles.
Human Subjects Research
All research involving human participants must have been approved by the authors' institutional review board or equivalent ethics committee(s), and that board must be named by the authors in the manuscript.
Originality
Only articles that have not been published previously, that have not been simultaneously submitted elsewhere, and that are not under review for another publication should be submitted to this journal. The journal editors will assume that submission of an article to this journal implies that all the foregoing conditions are applicable.
Grey literature (e.g. conference papers, presentations, white papers, blog posts, and other unpublished work) may be submitted for review and publication in JLSC if all copyrights still reside with the submitting author(s). Preference will be given to works for which publication in JLSC will expand access or add value to the work. As a professional courtesy, authors should indicate if they are submitting such work, and if and where the work currently appears or has appeared. This information should be shared in the author’s cover letter at the time of initial submission.
Plagiarism
JLSC does not accept articles containing material plagiarized from other publications or authors.
For the purposes of this policy, plagiarism is defined as copying of or reliance on work — including text, images and data — by others or yourself without proper attribution. Please be aware that you can plagiarize yourself; you must provide proper attribution in all cases where your previously published material or previously used data or images are included in your manuscript. (See JLSC’s Originality Policy.)
Plagiarism detected prior to publication will cause rejection of your manuscript. Plagiarism detected after publication will cause the published article to be corrected to state that it contains plagiarized material; in extreme cases of plagiarism, the publication will be retracted at the Editors’ discretion, and the reason for retraction stated on the journal's website. (See JLSC's policy of Correction, Retraction, and Removal.)
JLSC does not consider the following situations to be plagiarism when proper attribution is made:
- Translations into English of a previously published paper not in English;
- Publication of all or part of a revised thesis or dissertation;
- Publication of a paper previously made public as a conference presentation, white paper, technical report, or preprint.
JLSC follows workflows developed by the Committee on Publication Ethics (COPE) [PDF] to deal with cases of plagiarism.
Language
At this time, JLSC publishes only English-language articles and can accept only English-language manuscripts.
However, JLSC seeks a global authorship, and welcomes submissions from authors worldwide, including those for whom English is an additional language.
Artificial Intelligence Generated Content (AIGC)
Overview
Artificial Intelligence (AI) and Generative AI (GenAI) are rapidly reshaping open scholarship by transforming how knowledge is created, shared, accessed, and evaluated. While traditional AI analyzes existing data, GenAI goes further by generating new, original content based on learned patterns and where models are trained using vast amounts of data which may or may not be known to the user. As GenAI is integrated more widely and quickly into academic workflows, this ability raises crucial questions for scholarly communication, including authorship, integrity, transparency, and research reliability. Recognising these issues, the editorial team of the Journal of Librarianship and Scholarly Communication (JLSC), commits to monitoring and reviewing developments across the professional literature and any updates to the Committee on Publication Ethics (COPE) guidelines for AI use and will revise this policy to reflect the most current best practice to support openness, honesty and transparency in research. Updates will be reflected via a time-stamp on the webpage. It is expected that content will be reviewed every 12 months by the editorial board, or more frequently if required.
We acknowledge and support that the evaluation, understanding, and teaching of AI tools is of utmost importance to the field of librarianship, and encourage all authors, reviewers, editors, and readers to approach these topics with open engagement but also with critical discernment. When Artificial Intelligence Generated Content (AIGC) tools are used, we believe full disclosure should apply, with information provided regarding the name, version, and provider of the tool or model, and why and how it was applied to the research conception, writing, and editing of a manuscript.
Definitions
‘AI’, ‘AIGC’, and ‘automation’ are not interchangeable.
AI-assisted search engines or “agents” refers to search engines utilising AI to retrieve, summarise, categorise and extract parts of records in response to a (sometimes iterative) search query. The influence the tool exerts on the results retrieved and how they are presented is unclear at this point. AI tools can present or create factually incorrect results or nonsensical “information”.
AIGC refers to unique content created by tools using predictions made via machine learning from LLMs (large language models) or SMLs (small language models). AIGC tools include, but are not limited to, tools that provide functions for text generation, image generation, resource discovery, text-to-video, etc., and other tools trained on LLMs (LLMs) or SMLs that generate unique content based on predictions. This also applies to AIGC add-ons within software.
Automation refers to rules based software, and includes tools like spelling and grammar checkers.
This policy covers the use of AIGC and AI whether by authors, editors, or peer reviewers. Use of automation is not included in this policy and is permitted by JLSC.
Should you have any concerns, questions, or issues regarding generative AI within JLSC publications, please contact editors@jlsc-pub.org
Data Privacy & AI Training Models
Authors should proceed with caution when uploading research data and/or authored content into generative AI tools, and always avoid inputting sensitive or confidential data. Data privacy and intellectual property ownership guidelines vary by tool, are often updated regularly, may be dependent on geographic location (of both the tool and the individual using it), and are not always evident. There is the potential that the creator of the tool retains the right to use some or all of the content fed into it.
Openly accessible academic publications, such as those published by JLSC, are frequently utilized by various entities for AI model training. This practice is widespread and often occurs without the explicit permission of authors or publishers.
Work published in JLSC is assigned a CC BY 4.0 License, allowing you to contribute to the global dissemination of open and free knowledge. However, please be aware that this openness may also result in your work being incorporated into AI training datasets (See Creative Commons’ Understanding CC Licenses and AI Training: A Legal Primer). We encourage authors to consider this information when deciding to publish. JLSC does not engage in or profit from the use of your work for AI training purposes.
For Authors
At this time, JLSC allows the use of generative AI as tools to support authors’ original research and submitted manuscripts. Manuscripts must be written by human authors and AI tools should only be used to support the author’s own ideation, critical thinking, and creative processes.
JLSC is in agreement with the following statement from COPE:
AI tools cannot meet the requirements for authorship as they cannot take responsibility for the submitted work. As non-legal entities, they cannot assert the presence or absence of conflicts of interest nor manage copyright and license agreements.
See COPE’s Full statement on AI authorship.
Manuscripts cannot list AI tools as coauthors because they can not take responsibility for the content when submitting to JLSC.
Authors are prohibited from using AI tools to create falsified data and content, including text, data, images, etc., unless for the explicit purposes of illustrating a specific and stated argument. Authors may use AI tools to sort, categorise, clean, order or present data, provided the results are a true representation of the data collected and have been verified as such by the author.
If authors submitting to JLSC have used AIGC in any portion of a manuscript, including text, data, images, graphics, videos, citations or translations, the tool and its use must be described in detail in the methods section and other sections of the manuscript when appropriate. This is inclusive of prompts used, the language the prompt was written in, and the full text of the original AIGC must be attached as an appendix or as supplemental material.
In the submission process, authors will be asked to complete the following statement declaring any AIGC in the manuscript:
During the preparation of this work the author(s) used [NAME OF TOOL /MODEL/SERVICE] in order to [REASON]. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the factual accuracy and originality of the material.
It is essential to disclose not just the version used, but also which specific model, when it was used, and by whom—especially since models like GPT-3.5 and GPT-4 (available in the same version of ChatGPT) can produce different responses to the same prompt. Tracking these details is crucial for transparency, as models evolve quickly and their outputs may change over time or with different users.
If authors discover sources through the use of AI tools, they must access those sources directly, either the available preprint, repository Author Accepted Manuscript (AAM) or the published Version of Record (VoR), and not rely on or cite AI generated summaries in order to use and cite them in their manuscripts. As with standard manuscript submission, the author is responsible for the accuracy of all information provided by the tool.
For examples of how to cite AIGC tools please see this helpful page created by the Journal of New Librarianship (See Authors, Citation Formatting).They also offer a useful author checklist for attributing AI.
For Editors
Editors may search AI supported discovery tools with keywords of their own design to assist in finding expert researchers in a particular field, much as they would consult resources such as JLSC’s list of self-registered peer reviewers, Google Scholar, or Scopus to find names of prominent authors in a given area of expertise. JLSC editors are aware of many of the inherent biases found in AI tools and consult a number of different sources when sourcing peer reviewers.
Initial assessments and selection of peer reviewers by JLSC editors will not be done by AI tools and manuscripts submitted to JLSC will not be uploaded into such tools. Author’s manuscripts will be treated with confidentiality throughout the editorial and peer review process. As it is currently unclear how data ingested in AI tools is stored and reused, sharing any part of the manuscript including text, figures, graphs, and images potentially violates confidentiality. Editors will not use AI detection tools for the same reason.
For Peer Reviewers
JLSC expects reviewers to be responsible for the content of their reviews and does not allow the use of AI tools in the peer review of manuscripts. This includes tools to generate summarisation, annotation, critique, and feedback. Among the reasons are:
- Uploading manuscripts into AIGC tools potentially compromises authors' proprietary rights and confidentiality.
- AIGC tools are trained on past data whereas the peer review process is concerned with the evaluation of new research and the novel application of methodologies which can only be properly assessed by expert researchers in the field.
- AIGC tools at this point in time can replicate and amplify human bias rather than correct it in the peer review process.
- AIGC tools are often created and owned by private commercial interests and their processes are not transparent or interpretable.
Peer reviewers will be required to acknowledge JLSC’s policy on the use of AI in peer review when accepting manuscripts for review and take full responsibility for the reports they provide to JLSC.