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Kutadgu Open Access Academic Publishing System
Open access · Open peer review

Submit your work

This is an independent publishing venue where blind review is not practised. Reviewers stand behind their assessments by name; the decision and its grounds are published permanently alongside the work. You may submit once you have read the conditions below.

1

Application

You submit work meeting the conditions through this form. A desk check follows.

2

Access

If accepted, editing access is opened for that one work only.

3

Review

You may suggest reviewers. Every name, decision and report is published openly.

4

Decision

2 acceptances give international validity; 2 rejections move the work to the non reviewed track.

Conditions

Submission conditions

Author standing

Every author must hold at least a doctoral degree. This condition is required of each co author individually, whatever the number of authors.

  • ORCID required for every author (check digit is validated)
  • Scopus Author ID required for every author

%15

Similarity ceiling. Must be documented with an iThenticate, Turnitin or intihal.net report.

  • Overall similarity at most 15%
  • Similarity cannot all come from one source: at most 5% from a single source
  • An accessible link to the report is required

Use of artificial intelligence

Using AI tools is not prohibited; the extent must be declared and the use must remain within the relevant ethical guidance.

Figures and tables

Figures and tables must be supplied separately and at high resolution rather than embedded in the text; they appear as enlargeable links in the published work.

  • A shared folder link is sufficient

Data and analysis

For empirical work the data set and the software and code used in the analysis must be shared.

  • R, EViews, MATLAB, Orange, Stata, SPSS, Python
  • Reproducibility is essential

Transfer of copyright

Authors submitting to this system are deemed to have transferred all rights in the work to the Kutadgu publishing system. Publication is open access (CC BY 4.0).

The full editorial policies →
Form

Application form

Applicant (corresponding author)

Access details are sent to this person.

The access link is sent to this address, so use an institutional address you can reach.

You can take your Scopus ID from the authorId= value in your profile link; pasting the whole link also works.

Co authors

Every co author must also hold at least a doctoral title; ORCID and Scopus Author ID are required for each.

The work

Similarity report

Overall similarity at most 15%; at most 5% from any single source.

Upload the PDF of the report to an accessible folder and enter the link here.

Artificial intelligence declaration

Use is not prohibited; failing to declare it is not acceptable. This declaration is published with the work.

If you wish to check your work against several language models before submitting: open the review prompts.

Figures, data and analysis

Figures and tables are supplied separately at high resolution; for empirical work the data and code are shared.

These fields may be left empty for theoretical or conceptual work.

Suggested reviewers (optional)

You may suggest colleagues you know. Because every reviewer's name, decision and report is published, acquaintance cannot turn into favouritism. The final assignment rests with the editors.

Transfer of copyright

Your application has been received

Back to the works

AI review prompts

Run the prompts below separately on several language models. The judgement of a single model is not sufficient; models can produce different results for the same text. The aim is not a test of "being caught" but of seeing whether the text really carries your own intellectual contribution. Use the output to strengthen your work.

1. Comprehensive provenance analysisExamines the whole text for indicators of AI generation
You are a senior editor assessing the use of generative AI in academic texts. Analyse the text below impartially. Do not deliver a verdict; give an evidence based probability assessment. Address each of the following dimensions separately and give a DIRECT QUOTATION from the text for each: 1. VOCABULARY AND SYNTAX: Overly regular sentence length, uniform paragraph structure, frequency of low content formulas such as "it is important", "it is noteworthy", "plays a critical role". Assess the variance in sentence length. 2. ARGUMENT STRUCTURE: Are arguments actually developed, or are balanced looking generalisations merely listed? 3. USE OF SOURCES: Do citations support a specific step of the argument, or do they serve as decoration? 4. DISCIPLINARY DEPTH: Are there details, contested points or methodological limits that only someone working in the field would know? 5. ORIGINAL CONTRIBUTION: What idea does this text add to the literature that could not be assembled from another source? Say it in one sentence. If you cannot, say so plainly. 6. INCONSISTENCY: Is there discontinuity between parts of the text in style, terminology or format? Finish with: - A score from 0 to 10 for each dimension, with grounds - An overall assessment and your confidence level - Five concrete suggestions for strengthening the human contribution TEXT: """ [paste the full text of your work here] """
2. Adversarial testTests on the assumption that the first analysis may be wrong
It has been claimed that the academic text below was produced by artificial intelligence. You are the party arguing AGAINST that claim: look for evidence that the text was written by a human. Examine in particular: - Passages containing personal judgement, hesitation or admission of limits - Concrete field specific details that could not be recited from memory - Unexpected examples and unusual pairings of concepts - Linguistic irregularity, a natural distribution of long and short sentences - Passages resting on the author's own data or particular observation Then be honest: is this evidence enough to refute the claim? If not, which passages remain suspect? Rely only on the text; do not be charitable. TEXT: """ [paste the text] """
3. Paragraph by paragraph mappingShows which paragraphs are suspect, one by one
Examine the text below paragraph by paragraph, numbering each. For every paragraph give one line: [paragraph no] | [human / mixed / likely AI] | [confidence 0-100] | [the single most decisive indicator behind this call] When finished: - List the three most suspect paragraphs and say what is missing in each - Give the proportion of suspect paragraphs as a percentage - Set out concretely how those paragraphs could be strengthened TEXT: """ [paste the text] """
4. Fact checking and fabricated source scanChecks the risk of non existent citations and false information
Check every factual claim and every citation in the academic text below. This check is essential because generative AI tools can produce non existent sources and incorrect bibliographic details. For each source state: - Is the reference internally consistent? (author, year, journal, volume, pages) - Do you have knowledge that this work actually exists? If unsure, say "could not be verified"; do not invent. - Does the claim attributed to this source match the source's known content? Also: - List numerical claims one by one and flag the suspect ones - List claims made without a citation that require one - Flag over general and unfalsifiable statements Finish with a separate list of sources that could not be verified. TEXT AND BIBLIOGRAPHY: """ [paste the text and bibliography] """
5. Authorship testMeasures intellectual ownership of the text
After reading the text below, produce twelve questions to put to its author. The questions should be such that someone who genuinely thought through and wrote the text can answer easily, while someone who had a tool produce it would struggle. The questions should probe: - Why was this theoretical framework chosen, which alternative was set aside and why? - What are the known limits of the method, and how did the author deal with them? - If a given finding runs against expectation, what is the author's explanation? - What exactly is the link between a given work in the bibliography and a given claim in the text? - If this study were to be falsified, what evidence would do it? Having produced the questions, assess whether the text itself answers them. Questions with no answer in the text mark the points where the author should strengthen the work. TEXT: """ [paste the text] """

How to read the results: None of these tools produces conclusive proof; language models can mistake human writing for AI output and the reverse. An "AI detection score" alone is therefore never grounds for rejection here. The criterion is that the work carries an original intellectual contribution and that any use is declared.