Athena: Journal of Social, Culture and Society recognizes that artificial intelligence (AI), generative artificial intelligence, large language models (LLMs), and other automated tools are increasingly used in scholarly research, data analysis, writing, editing, and publication workflows. Athena permits responsible use of such technologies provided that their use is transparent, ethically appropriate, and subject to meaningful human oversight.

Generative AI systems, chatbots, large language models, software applications, algorithms, and other automated tools must not be listed as authors or co-authors of manuscripts submitted to Athena.

Authorship requires accountability, approval of the final manuscript, responsibility for the integrity of the work, management of competing interests, and the ability to respond to questions concerning the research. Automated systems cannot satisfy these responsibilities.

Authors remain fully responsible for all content submitted to Athena, regardless of whether AI or automated technologies were used during research or manuscript preparation.

Authors are responsible for verifying:

• the factual accuracy of AI-assisted content;
• the validity of research interpretations and conclusions;
• the accuracy of quotations, numerical values, statistics, tables, and figures;
• the authenticity and accuracy of all citations, references, URLs, and DOIs;
• the originality of submitted material;
• compliance with copyright, privacy, confidentiality, and intellectual-property requirements;
• the absence of fabricated, falsified, misleading, discriminatory, or unsupported information; and
• compliance with Athena's publication ethics and research-integrity policies.

Authors must transparently disclose substantive use of generative AI or similar automated content-generation tools in preparing a manuscript.

Disclosure is expected when AI has materially contributed to:

• drafting or substantially rewriting manuscript text;
• generating summaries or literature syntheses;
• generating or substantially modifying figures, illustrations, or other research content;
• producing computer code used materially in the study;
• generating or transforming research data;
• performing substantive analytical or interpretive tasks; or
• otherwise contributing materially to the scholarly content of the manuscript.

Routine use of tools for spelling correction, grammar correction, formatting, reference formatting, or basic language polishing normally does not require a separate generative-AI disclosure, provided that the tools do not substantively generate scholarly content.

Where disclosure is required, authors should clearly identify:

• the name of the AI or automated tool used;
• the purpose for which it was used;
• the stage of research or manuscript preparation in which it was used;
• the nature of its contribution; and
• where relevant, how the authors verified, reviewed, or validated its output.

When AI, machine learning, natural language processing, computer vision, automated decision systems, or other computational technologies constitute part of the research methodology itself, their use should be described with sufficient methodological detail to allow readers to understand and evaluate the research.

Where relevant, authors should report:

• the tool, model, software, algorithm, or system used;
• the model or software version where relevant;
• input data and important preprocessing procedures;
• parameters, prompts, configurations, or procedures necessary to understand the analysis;
• validation or verification procedures;
• relevant limitations and potential sources of bias; and
• appropriate information necessary to support reproducibility or methodological transparency.

Generative AI systems must not be treated as authoritative scholarly sources and should not replace original research literature, primary sources, datasets, official records, or other appropriate evidence.

Authors must independently locate, read, and verify the original scholarly sources underlying factual claims. AI-generated references, quotations, authors, article titles, journal names, DOIs, or other bibliographic information must never be included without verification against the original source.

The use of AI or automated tools is unacceptable when it results in, facilitates, or conceals research or publication misconduct. Examples include:

• fabrication or falsification of research data;
• fabrication of references, quotations, findings, participants, or evidence;
• manipulation or creation of misleading research images or visual evidence;
• plagiarism or inappropriate paraphrasing of copyrighted or scholarly material;
• concealment of substantive AI-generated scholarly content where disclosure is required;
• violation of participant confidentiality or privacy;
• uploading confidential, sensitive, proprietary, or personally identifiable research information into external AI services without appropriate authorization; or
• any other use that compromises research integrity, transparency, copyright, ethical standards, or the reliability of the scholarly record.

Athena may use automated tools to assist editorial integrity screening, including similarity detection, AI-writing indicators, reference checking, or other research-integrity checks.

Where appropriate, Athena may use Turnitin as part of its manuscript-integrity screening workflow.

Automated results are treated as screening indicators rather than final determinations. Editorial personnel review and interpret relevant results before any action concerning a manuscript is taken.

Manuscripts received for peer review are confidential documents. Reviewers must protect manuscript content, unpublished findings, author information, and other confidential materials.

Reviewers must not upload confidential manuscripts or substantial portions of them to external generative AI systems for the purpose of generating peer-review reports, evaluations, recommendations, or substantive scholarly assessments.

Reviewers remain personally responsible for the originality, accuracy, objectivity, evidence, and scholarly judgment contained in their review reports.

Editors and editorial staff must protect the confidentiality of submitted manuscripts and peer-review communications.

Confidential manuscripts must not be uploaded to external generative AI systems for the purpose of generating substantive editorial assessments, peer-review evaluations, or publication decisions.

Editorial decisions must remain under human responsibility. Automated tools may assist administrative or integrity screening activities, but acceptance, revision, rejection, correction, and other substantive editorial decisions must be made or verified by qualified human editors.

If editors identify credible concerns regarding undisclosed or inappropriate use of generative AI, authors may be asked to provide clarification regarding the tools used, the extent of their use, relevant research records, original data, source materials, or other supporting information.

Editorial action will depend on the nature and seriousness of the concern. Action may include requesting clarification, disclosure, correction, revision, additional verification, rejection, or post-publication action where necessary under Athena's Publication Ethics and Corrections and Retractions policies.