{"id":69259,"date":"2025-07-23T14:22:52","date_gmt":"2025-07-23T12:22:52","guid":{"rendered":"https:\/\/www.audiotranskription.de\/citing-chatgpt-and-other-ai-content-scientifically-a-practical-guide-for-researchers\/"},"modified":"2025-07-23T14:22:52","modified_gmt":"2025-07-23T12:22:52","slug":"citing-chatgpt-and-other-ai-content-scientifically-a-practical-guide-for-researchers","status":"publish","type":"post","link":"https:\/\/www.audiotranskription.de\/en\/citing-chatgpt-and-other-ai-content-scientifically-a-practical-guide-for-researchers\/","title":{"rendered":"Citing ChatGPT and other AI content scientifically: A practical guide for researchers"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243; row_bg_color=&#8221;bg&#8211;color&#8211;bg-1&#8243; row_boxpadding=&#8221;vc_boxpadding&#8221;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Specify AI correctly - here&apos;s how<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<\/p>\n<ul class=\"icon-list icon-list--chevron\" data-sourcepos=\"7:1-11:0\">\n<li data-sourcepos=\"7:1-7:133\"><strong>No direct quotation:<br \/>\n<\/strong><span style=\"font-weight: 400;\">LLM responses are not quotable like conventional text sources (book, academic essay, newspaper article) or personal communications.<\/span><\/li>\n<li data-sourcepos=\"8:1-8:235\"><strong><b>Describe the LLM application in the method section and document the dialog in the appendix:<br \/>\n<\/b><\/strong><span style=\"font-weight: 400;\">Name the tool (e.g. ChatGPT-4o, OpenAI), the purpose (e.g. for brainstorming) and how you used it (e.g. central prompts, procedure). In some LLM-supported research methods (such as hybrid text interpretation; cf. Kr\u00e4hnke et al. 2025), the entire chat dialog (prompts and outputs) is listed in the appendix as part of the method documentation, but not directly cited as a source.<\/span><\/li>\n<li data-sourcepos=\"9:1-11:0\"><strong>List in the bibliography:<br \/>\n<\/strong>Reference the LLM itself correctly, e.g:<br \/>\nOpenAI. (2023). <em>ChatGPT<\/em> (Version 4o) [Large language model]. <a href=\"https:\/\/chat.openai.com\/\" target=\"_blank\" rel=\"noopener\">https:\/\/chat.openai.com<\/a><\/li>\n<\/ul>\n<p data-sourcepos=\"12:1-12:114\"><strong>Important:<\/strong> Always check specific requirements (university, publisher)! Details &amp; reasons can be found below:<\/p>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_top=&#8221;vpt-7&#8243; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Introduction<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<span style=\"font-weight: 400;\">Large language models such as ChatGPT, Claude or Gemini support literature research, text drafts or qualitative data analysis and AI supports automatic transcription. These tools raise a key question: how to document and cite generated content correctly in scientific papers, as the transparent documentation of AI use is now standard good scientific practice.  <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Since LLM responses are not permanently and identically retrievable like books or articles, they are not considered bibliographically verifiable sources. Nor should they be treated as &#8220;personal communication&#8221;. This is because the content of generative AI comes from machines and is neither stable nor replicable. For reasons of transparency, however, it must be documented where and how exactly the LLM was used in the research process: in the methods section, through complete prompts and outputs in the appendix and through a formal inclusion of the tool used in the bibliography.<\/span><\/p>\n<p>This article summarizes the current recommendations of the common styles (APA, Harvard) and shows how you can make the use of LLM transparent in your research. You will also receive formulations and templates for your method section based on practical examples. We present this detailed guideline because &#8211; in view of the rapid development of AI tools and the scientific discussion about them &#8211; various approaches to citation exist, but some common recommendations do not, in our opinion, take sufficient account of aspects such as reproducibility or methodological embedding. This article therefore shows a way forward that takes particular account of the principles of good scientific practice.<\/p>\n<p data-sourcepos=\"5:1-5:87\"><strong>Supplemented 26.05.25: Graduated transparency: Differentiated approaches to documenting AI usage<\/strong><\/p>\n<p data-sourcepos=\"7:1-7:1078\">It is important to emphasize that the scientific debate on how to deal with AI use is still in flux. In addition to the specific question of <em>how<\/em> to cite AI content, there are also approaches that suggest a differentiation according to <em>the type and scope<\/em> of AI use. For example, the editors of the Zeitschrift f\u00fcr Evaluation (ZfEv) suggest in their current <a href=\"https:\/\/www.degeval.org\/zeitschrift-fuer-evaluation\/hinweise-fuer-autor-innen\/\" target=\"_blank\" rel=\"noopener\">notes<\/a> and an <a href=\"https:\/\/www.degeval.org\/fileadmin\/content\/Z05_ZfEv\/Hinweise_zur_KI-Nutzung_ZfEv_Dezember_2024.pdf\" target=\"_blank\" rel=\"noopener\">AI handout<\/a> (as of December 2024) that different requirements should be placed on the documentation depending on whether AI was only used as a writing assistant, to create content, to support content or in empirical work. This can range from no necessary labeling (in the case of pure writing assistance) to classic source references to detailed descriptions in the methods section or a separate disclosure section. Regardless of the approach chosen, the primary objective remains to ensure traceability and scientific integrity.<\/p>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >APA citation style: focus on methodological transparency<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]The <strong data-start=\"1403\" data-end=\"1447\">American Psychological Association (APA)<\/strong> recommends in its guideline (APA, 2023):<\/p>\n<blockquote><p>&#8220;If you&#8217;ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.&#8221;<br \/>\n<em>Source: <a href=\"https:\/\/apastyle.apa.org\/blog\/how-to-cite-chatgpt\" target=\"_blank\" rel=\"noopener\">https:\/\/apastyle.apa.org\/blog\/how-to-cite-chatgpt<\/a><\/em><\/p><\/blockquote>\n<p>In addition, Columbia College provides these implementation tips:<\/p>\n<blockquote><p>&#8220;APA recommends that you include an explanation of how you used ChatGPT, and an Appendix (or Appendices) containing the full text of your prompt(s) and output(s).&#8221;<br \/>\n<em>Source: <a href=\"https:\/\/columbiacollege-ca.libguides.com\/c.php?g=713274&amp;p=5355771\" target=\"_blank\" rel=\"noopener\">https:\/\/columbiacollege-ca.libguides.com\/c.php?g=713274&amp;p=5355771<\/a><\/em><\/p><\/blockquote>\n<p>In concrete terms, this means<\/p>\n<p class=\"\" data-start=\"1743\" data-end=\"1790\"><strong>Information in the methods section or in a comparable chapter:<\/strong><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul data-start=\"1793\" data-end=\"1996\">\n<li class=\"\" data-start=\"1793\" data-end=\"1853\">\n<p class=\"\" data-start=\"1795\" data-end=\"1853\">Which AI tool was used (e.g. ChatGPT-4o)?<\/p>\n<\/li>\n<li class=\"\" data-start=\"1856\" data-end=\"1924\">\n<p class=\"\" data-start=\"1858\" data-end=\"1924\">What for (e.g. brainstorming, text drafts, summaries)?<\/p>\n<\/li>\n<li class=\"\" data-start=\"1927\" data-end=\"1996\">\n<p class=\"\" data-start=\"1929\" data-end=\"1996\">How (central prompt, example of a generated response)?<\/p>\n<\/li>\n<li>No direct citation of individual AI answers, as they are not available in a stable manner (i.e. they are NOT always answered in the same way).<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong data-start=\"2000\" data-end=\"2010\">Appendix:<\/strong><\/p>\n<ul>\n<li data-start=\"2029\" data-end=\"2128\"><span style=\"font-weight: 400;\">Complete AI dialogs (prompt + response), (e.g. for hybrid interpretation).<\/span><\/li>\n<\/ul>\n<p class=\"\" data-start=\"2220\" data-end=\"2267\"><strong data-start=\"2220\" data-end=\"2265\">Example of the reference entry according to APA<\/strong><\/p>\n<blockquote data-start=\"2268\" data-end=\"2359\">\n<p class=\"\" data-start=\"2270\" data-end=\"2359\">OpenAI. (2023).  <em data-start=\"2286\" data-end=\"2333\">ChatGPT (Version 4.0) [Large language model].<\/em> <a class=\"\" href=\"https:\/\/chat.openai.com\/\" target=\"_new\" rel=\"noopener\" data-start=\"2334\" data-end=\"2359\">https:\/\/chat.openai.com<\/a><\/p>\n<\/blockquote>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Harvard citation style: focus on formal bibliographic coverage<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<\/p>\n<p class=\"whitespace-pre-wrap break-words\">The <strong data-start=\"2442\" data-end=\"2477\">University College Dublin (UCD)<\/strong> recommends the <strong data-start=\"2496\" data-end=\"2518\">Harvard citation style<\/strong> (UCD Library, 2025):<\/p>\n<blockquote>\n<p class=\"whitespace-pre-wrap break-words\">&#8220;When referencing AI-generated text in Harvard UCD, you should credit the creator of the AI tool as the author, using both an in-text citation and a reference list entry. If a shareable URL is available, please include it in the reference list entry. In the absence of a shareable URL, include the chat session with the AI tool as an appendix and refer readers to this appendix when citing the AI-generated text.&#8221; <em>Source: <a class=\"underline\" href=\"https:\/\/libguides.ucd.ie\/harvardstyle\/harvardgenAI?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">https:\/\/libguides.ucd.ie\/harvardstyle\/harvardgenAI?utm_source=chatgpt.com<\/a><\/em><\/p>\n<\/blockquote>\n<p class=\"whitespace-pre-wrap break-words\"><span style=\"font-weight: 400;\">Harvard style requires that the developer of the AI system is cited as the author. This is done by in-text citation and entry in the bibliography. If the URL is missing, the complete documentation of the chat session is recommended as an attachment.<\/span><\/p>\n<p class=\"\" data-start=\"3375\" data-end=\"3426\"><strong data-start=\"3375\" data-end=\"3424\">Example of the Harvard reference entry<\/strong><\/p>\n<blockquote data-start=\"3427\" data-end=\"3551\">\n<p class=\"\" data-start=\"3429\" data-end=\"3551\">OpenAI (2023) <em data-start=\"3443\" data-end=\"3490\">ChatGPT (Version 4.0) [Large language model].<\/em> Available at: <a class=\"\" href=\"https:\/\/chat.openai.com\/\" target=\"_new\" rel=\"noopener\" data-start=\"3505\" data-end=\"3530\">https:\/\/chat.openai.com<\/a> (Accessed: [date]).<\/p>\n<\/blockquote>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Recommended practice in academic papers<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<\/p>\n<p data-sourcepos=\"23:1-23:344\"><strong>Why you shouldn&#8217;t treat AI answers like quotes<\/strong><\/p>\n<p data-sourcepos=\"23:1-23:344\"><span style=\"font-weight: 400;\">Many researchers ask themselves the question: Can or should I simply insert the answer from ChatGPT into my work like a quote from a book? The clear scientific answer is: No, AI answers are not citable sources in the traditional sense. Here is a summary of the main reasons:<\/span><\/p>\n<ol data-sourcepos=\"25:1-29:0\">\n<li data-sourcepos=\"25:1-25:433\"><strong>No stability and reproducibility:  <\/strong><span style=\"font-weight: 400;\">The most important practical reason is that AI responses are not stable. Unlike a printed text, an AI such as ChatGPT does not provide identical answers to the same question (prompt). Even if you save an answer, other readers cannot reliably replicate or verify that specific answer. However, scientific evidence must be verifiable.<\/span><\/li>\n<li data-sourcepos=\"26:1-26:500\"><strong>Lack of scientific authorship:<\/strong> <span style=\"font-weight: 400;\">AI systems are tools, not authors. They lack human judgment, responsibility and the ability to stand up for their statements in scientific discourse. As the German Research Foundation (DFG, 2023) emphasizes, authorship requires agency and responsibility, which can only be found in humans (see also Buck, 2025, p. 87). AI does not have its own &#8220;opinion&#8221; or scientific position (Buck, 2025, p. 91).<\/span><\/li>\n<li data-sourcepos=\"27:1-27:384\"><strong>Unsuitable as a &#8220;personal message&#8221;:<\/strong> <span style=\"font-weight: 400;\">Sometimes it is suggested to treat AI responses as &#8220;personal communication&#8221;. That is not correct either. This category is intended for communication between people that is not publicly accessible but can be traced (e.g. emails, interviews). An AI answer does not fit here (see notes from the Harvard Library).<\/span><\/li>\n<li data-sourcepos=\"28:1-29:0\"><strong>No scientific contribution:<\/strong> <span style=\"font-weight: 400;\">Simply copying an AI answer does not constitute a research achievement in itself. Scientific work requires a critical examination of information, its classification and the development of one&#8217;s own conclusions. The power lies in the way you use AI as a tool and evaluate and integrate the results.<\/span><\/li>\n<\/ol>\n<p data-sourcepos=\"30:1-30:45\"><strong>The right approach is:<\/strong><\/p>\n<ul data-sourcepos=\"32:1-35:0\">\n<li data-sourcepos=\"32:1-32:281\"><strong>Transparency in the methods section:<\/strong> <span style=\"font-weight: 400;\">Describe exactly which AI tool (with version, developer) you have used, for what purpose and in what way. Explain your approach, any key prompts and how you checked and used the results of the AI.<\/span><\/li>\n<li data-sourcepos=\"33:1-33:377\"><strong>Referencing the tool:  <\/strong><span style=\"font-weight: 400;\">List the AI tool used (not the individual answer!) correctly in the bibliography. Depending on the citation style (e.g. according to Harvard\/UCD), the developer (e.g. OpenAI) is then formally named in the author position. This serves to identify the tool, not to attribute authorship to the AI for the output.<\/span><\/li>\n<li data-sourcepos=\"34:1-35:0\"><strong>Documentation in the appendix (optional\/depending on method):  <\/strong><span style=\"font-weight: 400;\">For certain approaches, such as hybrid interpretation (Kr\u00e4hnke et al., 2025), in which the dialog process itself is part of the method, it can be useful to document the prompts and responses in the appendix in order to ensure the traceability of the process. However, this serves the purpose of method transparency, not the proof of a substantive statement by the AI.<\/span><\/li>\n<\/ul>\n<p data-sourcepos=\"36:1-36:222\"><strong>To summarize:<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">Treat AI as a tool whose use you must document for transparency reasons, but not as a source that you can cite directly to support substantive arguments. As the citation standards for AI tools are still in a state of flux, you should also observe the current requirements of your university, department or publisher. It is important that your own scientific achievement remains clearly recognizable and that readers can follow your steps.<\/span><\/p>\n<h3 class=\"text-lg font-bold text-text-100 mt-1 -mb-1.5\" class=\"text-lg font-bold text-text-100 mt-1 -mb-1.5\" id=\"sample-formulations-for-the-method-section\">Sample formulations for the method section:<\/h3>\n<p class=\"whitespace-pre-wrap break-words\"><strong>Example 1 (general template):<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;In this work, [name of AI system] was used for [specific purpose, e.g. &#8216;identification of relevant literature&#8217;, &#8216;text summarization&#8217;, &#8216;data analysis&#8217;]. The complete dialog with the system, including all prompts used and responses generated, is documented in Appendix [X]. The use of AI was limited to [precise narrowing], while [aspects without AI support] were performed without AI support.&#8221;<\/span><\/p>\n<p class=\"whitespace-pre-wrap break-words\"><strong>Example 2 (specific application for hybrid interpretation with several LLMs):<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;For the qualitative analysis of the interview data, the method of hybrid interpretation with several dialogically integrated Large Language Models (LLMs) was used, as described by Kr\u00e4hnke et al (2025). As part of this approach, three different generative language model versions (Anthropics Claude 3.7 Sonnet, openAI&#8217;s ChatGPT-4o and Google&#8217;s Gemini 2.5 pro) were integrated into an iterative interpretation process in order to generate multiple perspectives on the data material. The text interpretation took place in three phases: initial, elaborating and synthesizing interpretation. All prompts and the generated LLM outputs are fully documented in Appendix B. The selection of the text passages to be interpreted, the critical evaluation of the AI-generated interpretations and the final analytical summarization were carried out by me as a researcher without AI support in order to ensure a methodologically controlled and object-appropriate analysis.&#8221;<\/span>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Special challenge: mediating AI systems<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<span style=\"font-weight: 400;\">MAXQDA AI Assist, MAXQDA Tailwind, DocumetAI, Queludra and similar tools in the field of qualitative research sometimes integrate their own system prompts, which remain invisible to users. In addition, it is usually not possible to identify which language model (ChatGPT, Claude etc.) was used in which version (4o, 01 preview, sonnet 3.5 etc.) in the background &#8211; because: the manufacturers have not developed their own AI models, but use existing tools, but usually do not make this transparent down to the last detail.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It should therefore be made clear in the methods section that the complete system prompts are not accessible and that it may remain unclear which LLM generated the answers. This lack of transparency can have methodological consequences: The non-reproducibility of the AI analysis makes it difficult to trace, hidden system prompts could influence the analysis unnoticed and some models only have limited knowledge (in terms of time\/content) from their respective training data. In order to make these limitations and biases transparent, it is necessary to document the specific work steps carried out with AI support. This includes a precise description of the software functions used (e.g. &#8220;text summarization&#8221;, &#8220;topic extraction&#8221;), the data entered and user instructions as well as the methods for critically reviewing the AI-generated results.<\/span><\/p>\n<h3 class=\"whitespace-pre-wrap break-words\" class=\"whitespace-pre-wrap break-words\" id=\"example-formulation\">Example formulation<\/h3>\n<blockquote>\n<p class=\"whitespace-pre-wrap break-words\">&#8220;<span style=\"font-weight: 400;\">MAXQDA AI Assist was used for the initial categorization as part of the qualitative content analysis. As the underlying system prompts and the language model used are not transparently disclosed, the analysis cannot be fully reproduced. To mitigate this limitation, we tested the AI proposals in a multi-stage discursive validation process (manual coding by two researchers, external discussion). Only those categories that passed were accepted. The AI support was limited to the exploratory phase; the final analysis and interpretation were carried out without AI.&#8221;<\/span><\/p>\n<\/blockquote>\n<h3 class=\"\" data-start=\"7663\" data-end=\"7703\" class=\"\" data-start=\"7663\" data-end=\"7703\" id=\"citation-of-mediating-systems\"><strong data-start=\"7667\" data-end=\"7701\">Citation of mediating systems<\/strong><\/h3>\n<blockquote data-start=\"7704\" data-end=\"7813\">\n<p class=\"\" data-start=\"7706\" data-end=\"7813\">VERBI Software. (2024).  <em data-start=\"7730\" data-end=\"7769\">MAXQDA AI Assist [Computer software].<\/em> <a class=\"\" href=\"https:\/\/www.maxqda.com\/products\/ai-assist\" target=\"_new\" rel=\"noopener\" data-start=\"7770\" data-end=\"7813\">https:\/\/www.maxqda.com\/products\/ai-assist<\/a><\/p>\n<\/blockquote>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Also cite the use of automatic transcription correctly!<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]So far in this article, we have mainly dealt with the citation of Large Language Models (LLMs) such as ChatGPT. However, the principle of transparent documentation also applies to other AI-based tools used in the research process. A key example of this is the automatic transcription of audio or video data. Here, too, it is essential to clearly describe their use in the methods section to ensure scientific traceability. For example, if you use the automatic transcription from audiotranskription.de &#8211; either via browser via f4x.audiotranskription.de or within the f4 2024 software &#8211; this should be documented.<\/p>\n<h3 id=\"what-belongs-in-the-methods-section\">What belongs in the methods section?<\/h3>\n<p><strong>Naming the tool<\/strong>: Specify the service or software used precisely (e.g. &#8220;AI-based transcription service from audiotranskription.de via f4x&#8221; or &#8220;automatic transcription function of the software f4 2024&#8221;), ideally with the date of use.<\/p>\n<p><strong>Purpose:<\/strong> Briefly describe the reason for use (e.g. &#8220;for the initial, time-saving transcription of expert interviews&#8221;).<\/p>\n<p><strong>Presentation of quality assurance:<\/strong> Since AI-based transcription can contain errors, the presentation of quality assurance is central. Have the automatically generated raw transcripts been fully checked against the recordings and manually corrected? According to which transcription rule system<a href=\"https:\/\/www.audiotranskription.de\/en\/content-related-semantic-transcription-rules\/\">(e.g. Dresing &amp; Pehl, 2023, content-semantic<\/a>) was the final transcript revised?<\/p>\n<h3 id=\"example-formulation-for-the-method-section\">Example formulation for the method section<\/h3>\n<blockquote><p>&#8220;The AI-based transcription service of audiotranskription.de was used for the initial transcription of the audio recordings (accessed via [f4x \/ f4 2024] on [date]). The raw transcripts generated in this way using automatic speech recognition were then checked and corrected manually by [person\/team] using the original recordings (e.g. in f4 2024 or Microsoft Word). The revision was carried out according to the rule system for content-semantic transcription by Dresing &amp; Pehl (2023) to ensure methodological fit and consistency.&#8221;<\/p><\/blockquote>\n<h3 id=\"example-of-the-transcription-service-software-entry-in-the-bibliography\">Example of the transcription service\/software entry in the bibliography<\/h3>\n<p><strong>Variant f4 Use via browser only:<\/strong><br \/>\naudiotranskription.de &#8211; Dr. Dresing &amp; Pehl GmbH. (year of use). Automatic transcription service [Web service]. Retrieved on [date of retrieval] from https:\/\/f4x.audiotranskription.de<\/p>\n<p><strong>Variant Use via software f4:<\/strong><br \/>\naudiotranskription.de &#8211; Dr. Dresing &amp; Pehl GmbH. (2024). f4 2024 (Version X.X) [Computer software]. https:\/\/www.audiotranskription.de<\/p>\n<p><strong>Example of the rule system entry:<\/strong><br \/>\nDresing, T. &amp; Pehl, T. (2023). Content-semantic transcription. In T. Dresing &amp; T. Pehl, Praxisbuch Interview, Transkription &amp; Analyse: Anleitungen und Regelsysteme f\u00fcr qualitativ Forschende (9th ed., p. [insert page number]). Dr. Dresing &amp; Pehl GmbH.[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243;][vc_column]<div class=\"vmb-3 wpb_content_element\" ><div class=\"heading heading--h2\"><h2 class=\"heading      \" >Literature<div class=\"heading__libero heading__libero--primary\"><\/div><\/h2><\/div><\/div>[vc_column_text]<\/p>\n<ul class=\"icon-list icon-list--chevron\">\n<li data-sourcepos=\"23:1-23:200\">American Psychological Association (APA). (2023, April 7). <em>How to cite ChatGPT<\/em>. APA Style Blog.  <a href=\"https:\/\/apastyle.apa.org\/blog\/how-to-cite-chatgpt\" target=\"_blank\" rel=\"noopener\">https:\/\/apastyle.apa.org\/blog\/how-to-cite-chatgpt<\/a><\/li>\n<li data-sourcepos=\"25:1-25:85\">Buck, Isabella. (2025). <em>Scientific writing with AI<\/em>. UVK Verlag (utb 6365).<\/li>\n<li data-sourcepos=\"27:1-27:251\">Columbia College Library. (n.d.). <em>ChatGPT &amp; Other AI Tools<\/em>. LibGuides. Retrieved April 4, 2025, from <a href=\"https:\/\/columbiacollege-ca.libguides.com\/c.php?g=713274&amp;p=5355771\" target=\"_blank\" rel=\"noopener\">https:\/\/columbiacollege-ca.libguides.com\/c.php?g=713274&amp;p=5355771<\/a><\/li>\n<li data-sourcepos=\"29:1-29:497\">German Research Foundation (DFG). (2023, September 21). <em>Statement by the Executive Committee of the German Research Foundation (DFG) on the influence of generative models for text and image production on the sciences and the DFG&#8217;s funding activities.<\/em> <a href=\"https:\/\/www.dfg.de\/resource\/blob\/289674\/ff57cf46c5ca109cb18533b21fba49bd\/230921-stellungnahme-praesidium-ki-ai-data.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/www.dfg.de\/resource\/blob\/289674\/ff57cf46c5ca109cb18533b21fba49bd\/230921-stellungnahme-praesidium-ki-ai-data.pdf<\/a><\/li>\n<li data-sourcepos=\"31:1-31:243\">Harvard Library. (n.d.). <em>AI Guidance for Researchers: Citation<\/em>. LibGuides. Retrieved April 4, 2025, from <a href=\"https:\/\/guides.library.harvard.edu\/c.php?g=1330621&amp;p=10046069\" target=\"_blank\" rel=\"noopener\">https:\/\/guides.library.harvard.edu\/c.php?g=1330621&amp;p=10046069<\/a><\/li>\n<li data-sourcepos=\"31:1-31:243\">Editor of the Journal of Evaluation. (2024). Notes from the Zeitschrift f\u00fcr Evaluation on the use of artificial intelligence (as of December 2024). Retrieved from <a href=\"https:\/\/www.degeval.org\/zeitschrift-fuer-evaluation\/hinweise-fuer-autor-innen\/\" target=\"_blank\" rel=\"noopener\">https:\/\/www.degeval.org\/zeitschrift-fuer-evaluation\/hinweise-fuer-autor-innen\/<\/a><\/li>\n<li data-sourcepos=\"33:1-33:223\">Knowles, Alan M. (2024). Machine-in-the-loop writing: Optimizing the rhetorical load. <em>Computers and Composition<\/em>, <em>71<\/em>, 102826. <a href=\"https:\/\/doi.org\/10.1016\/j.compcom.2024.102826\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.1016\/j.compcom.2024.102826<\/a><\/li>\n<li data-sourcepos=\"35:1-35:250\"><span style=\"color: #000000;\">Kr\u00e4hnke, U.; Pehl, T. &amp; Dresing, T.. (2025). Hybrid interpretation of text-based data with dialogically integrated LLMs: On the use of generative AI in qualitative research. SSOAR Preprint. <a href=\"https:\/\/nbn-resolving.org\/urn:nbn:de:0168-ssoar-99389-7\" target=\"_blank\" rel=\"noopener\">https:\/\/nbn-resolving.org\/urn:nbn:de:0168-ssoar-99389-7<\/a> <\/span><\/li>\n<li data-sourcepos=\"35:1-35:250\">University College Dublin Library. (n.d.). <em>Harvard Style &#8211; Referencing generatively created AI text<\/em>. LibGuides. Retrieved April 4, 2025, from <a href=\"https:\/\/libguides.ucd.ie\/harvardstyle\/harvardgenAI\" target=\"_blank\" rel=\"noopener\">https:\/\/libguides.ucd.ie\/harvardstyle\/harvardgenAI<\/a><\/li>\n<li data-sourcepos=\"37:1-37:150\">VERBI Software. (2024). <em>MAXQDA AI Assist<\/em> [Computer software]. <a href=\"https:\/\/www.maxqda.com\/products\/ai-assist\" target=\"_blank\" rel=\"noopener\">https:\/\/www.maxqda.com\/products\/ai-assist<\/a><\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243; row_bg_color=&#8221;bg&#8211;color&#8211;grey-1&#8243; row_boxpadding=&#8221;vc_boxpadding&#8221;][vc_column][vc_column_text]You can quote this blog article as follows:<\/p>\n<p>Dresing, T., Kr\u00e4hnke, U., &amp; Pehl, T. (2025, April 4). <em>Citing ChatGPT and other AI content scientifically: A practical guide for researchers<\/em>. audiotranskription.de Blog. https:\/\/www.audiotranskription.de\/ki-richtig-zitieren[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row row_padding=&#8221;custom&#8221; row_padding_bottom=&#8221;vpb-7&#8243; row_bg_color=&#8221;bg&#8211;color&#8211;bg-1&#8243; row_boxpadding=&#8221;vc_boxpadding&#8221;][vc_column][vc_column_text] No direct quotation: LLM responses are not quotable like conventional text sources (book, academic essay, \u2026<\/p>\n","protected":false},"author":1,"featured_media":66161,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[399,380],"tags":[],"class_list":["post-69259","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-and-qualitative-analysis","category-f4analysis-tips-and-tutorials"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/posts\/69259","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/comments?post=69259"}],"version-history":[{"count":2,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/posts\/69259\/revisions"}],"predecessor-version":[{"id":69261,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/posts\/69259\/revisions\/69261"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/media\/66161"}],"wp:attachment":[{"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/media?parent=69259"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/categories?post=69259"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.audiotranskription.de\/en\/wp-json\/wp\/v2\/tags?post=69259"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}