Results of the summarizing process for the arXiv paper: 1707.04439v1

The study titled "Medical Theses and Derivative Articles: Dissemination Of Contents and Publication Patterns" conducted by Mercedes Echeverria, David Stuart, and Tobias Blanke investigates the dissemination of contents and publication patterns resulting from doctoral theses in universities. The research focuses on derivative articles that are published as a result of theses but have received little attention in previous studies. The authors aim to identify how derivative articles can be recognized through text analysis based on the full-text of medical theses and articles that share authorship. The methodology applied in this study involves exploiting the full-text articles according to organization of scientific discourse (IMRaD) using TurnItIn plagiarism tool. The findings reveal that the Discussion section's text similarity rate can differentiate between derivative and non-derivative articles. Additionally, it was found that 85% of derivative articles had their thesis author listed first, while supervisors participated as co-authors in 100% of such articles. Furthermore, 42% of authorship credit was retained by thesis authors in derivative articles compared to an average of 6.4 co-authors for non-derivative ones. The time differential regarding the year of thesis completion showed that 87.5% of derivative articles were published before or in the same year as their respective thesis completion date. These results suggest that doctoral students' publications are often derived from their dissertations, with supervisors playing a significant role in co-authoring these derivatives. Overall, this study sheds light on an important aspect of academic publishing within universities and highlights how derivative articles can be identified through text analysis methods. It provides valuable insights into publication patterns resulting from doctoral dissertations and emphasizes the significance of supervisor involvement in co-authoring derivatives.

• The study investigates dissemination of contents and publication patterns resulting from doctoral theses in universities
• Focuses on derivative articles that are published as a result of theses but have received little attention in previous studies
• Authors aim to identify how derivative articles can be recognized through text analysis based on the full-text of medical theses and articles that share authorship
• Methodology involves exploiting full-text articles according to organization of scientific discourse (IMRaD) using TurnItIn plagiarism tool
• Discussion section's text similarity rate can differentiate between derivative and non-derivative articles
• 85% of derivative articles had their thesis author listed first, while supervisors participated as co-authors in 100% of such articles
• 42% of authorship credit was retained by thesis authors in derivative articles compared to an average of 6.4 co-authors for non-derivative ones
• 87.5% of derivative articles were published before or in the same year as their respective thesis completion date
• Doctoral students' publications are often derived from their dissertations, with supervisors playing a significant role in co-authoring these derivatives.
• Study sheds light on an important aspect of academic publishing within universities and highlights how derivative articles can be identified through text analysis methods.

Exploring the Dissemination of Contents and Publication Patterns from Doctoral Theses

The study titled "Medical Theses and Derivative Articles: Dissemination Of Contents and Publication Patterns" conducted by Mercedes Echeverria, David Stuart, and Tobias Blanke investigates the dissemination of contents and publication patterns resulting from doctoral theses in universities. This research focuses on derivative articles that are published as a result of theses but have received little attention in previous studies.

Objectives

The authors aim to identify how derivative articles can be recognized through text analysis based on the full-text of medical theses and articles that share authorship.

Methodology

The methodology applied in this study involves exploiting the full-text articles according to organization of scientific discourse (IMRaD) using TurnItIn plagiarism tool.

Findings

The findings reveal that the Discussion section's text similarity rate can differentiate between derivative and non-derivative articles. Additionally, it was found that 85% of derivative articles had their thesis author listed first, while supervisors participated as co-authors in 100% of such articles. Furthermore, 42% of authorship credit was retained by thesis authors in derivative articles compared to an average of 6.4 co-authors for non-derivative ones. The time differential regarding the year of thesis completion showed that 87.5% of derivative articles were published before or in the same year as their respective thesis completion date.

Conclusion

These results suggest that doctoral students' publications are often derived from their dissertations, with supervisors playing a significant role in co-authoring these derivatives. Overall, this study sheds light on an important aspect of academic publishing within universities and highlights how derivative articles can be identified through text analysis methods. It provides valuable insights into publication patterns resulting from doctoral dissertations and emphasizes the significance of supervisor involvement in co-authoring derivatives.

Implications for Future Research

This research has implications for future studies related to academic publishing within universities as well as identifying ways to recognize derivatives through text analysis methods . Further investigations should focus on exploring other aspects such as differences between disciplines when it comes to publication patterns resulting from doctoral dissertations , or examining different types/sources/platforms used for disseminating content . Additionally , more research is needed to understand how supervisors’ involvement affects student outcomes when it comes to publishing derivatives .