insight - Research evaluation - # Determinants of scholarly impact of scientific publications

The Influence of Non-Scientific Factors on the Scholarly Impact of Scientific Publications

Q: How can research evaluation frameworks be redesigned to better capture the multidimensional aspects of research impact, beyond just scholarly impact?

Research evaluation frameworks can be redesigned by incorporating a more comprehensive set of metrics that go beyond just scholarly impact. This can include assessing the societal impact of research, such as contributions to policy-making, industry advancements, or societal well-being. Additionally, frameworks can consider the broader dissemination of research through non-traditional channels like social media, blogs, or public engagement activities. Collaborative and interdisciplinary research efforts can also be emphasized to capture the diverse impacts of research across different fields and sectors. By integrating qualitative assessments alongside quantitative metrics, research evaluation frameworks can provide a more nuanced understanding of research impact.

Q: What are the potential drawbacks or unintended consequences of over-emphasizing non-scientific factors in research evaluation, and how can these be mitigated?

Over-emphasizing non-scientific factors in research evaluation can lead to potential drawbacks and unintended consequences. One major concern is the risk of bias or subjectivity in evaluating these factors, which may not always align with the actual impact of the research. This could result in overlooking high-quality research with significant scholarly impact but fewer non-scientific attributes. Additionally, focusing too much on non-scientific factors may divert attention from the core scientific quality of research outputs, potentially compromising the integrity of the evaluation process. To mitigate these issues, it is essential to strike a balance between assessing non-scientific factors and maintaining a rigorous evaluation of research quality. Clear guidelines and criteria should be established for evaluating non-scientific attributes to ensure consistency and fairness in the assessment process. Transparency in decision-making and accountability in evaluating these factors can help mitigate biases. Furthermore, continuous monitoring and feedback mechanisms can help identify and address any unintended consequences of over-emphasizing non-scientific factors in research evaluation.

Q: What role can advanced bibliometric techniques, such as network analysis and topic modeling, play in providing a more holistic understanding of the knowledge flows and interdisciplinary connections underlying research impact?

Advanced bibliometric techniques, such as network analysis and topic modeling, can play a crucial role in enhancing our understanding of the knowledge flows and interdisciplinary connections underlying research impact. Network analysis can help visualize and analyze the relationships between researchers, institutions, and publications, providing insights into collaboration patterns and knowledge dissemination pathways. By mapping co-authorship networks and citation networks, researchers can identify key influencers and research clusters within a field. Topic modeling, on the other hand, can uncover thematic trends and emerging research areas by analyzing the content of publications. By identifying common themes and topics across a body of literature, researchers can gain a deeper understanding of the interdisciplinary connections and knowledge diffusion within and across disciplines. This can facilitate the identification of research gaps, interdisciplinary opportunities, and potential areas for collaboration. Overall, advanced bibliometric techniques offer powerful tools for researchers and evaluators to explore the complex dynamics of research impact, beyond traditional metrics. By leveraging these techniques, stakeholders can gain a more holistic and nuanced perspective on the multifaceted nature of research impact, leading to more informed decision-making and strategic planning in research evaluation and management.

Core Concepts

Non-scientific factors, such as author characteristics, publication venue, and bibliographic features, play a significant role in determining the scholarly impact of scientific publications, beyond their intrinsic quality as assessed by peer review.

Abstract

The study investigates the role of non-scientific factors alongside the quality of publications, as assessed by peer review, in determining their scholarly impact. The authors leverage data from the first Italian Research Assessment Exercise (VTR 2001-2003) and Web of Science citations to analyze the relationship between quality scores, non-scientific factors, and publication short- and long-term impact.

The key findings are:

Non-scientific factors, such as author characteristics, publication venue, and bibliographic features, significantly influence the scholarly impact of publications, even after controlling for their quality as assessed by peer review.
The quality scores assigned by peer reviewers have a marginal contribution in predicting the long-term scholarly impact, whereas the short-term impact (early citations) provides a substantial improvement in predictive ability.
Factors related to the byline (e.g., average author impact, presence of foreign authors), content and venue (e.g., journal impact factor, page length), and bibliography (e.g., number of references, cited articles' impact) consistently influence the long-term scholarly impact.
The journal where the publication appears plays an important role in determining the long-term impact beyond the journal's impact factor.

The findings suggest that research evaluation should consider both the quality and the non-scientific factors that influence the scholarly impact of publications, rather than relying solely on peer review of quality. This offers policymakers and research management insights in choosing appropriate evaluation methodologies.

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Stats

The average age of cited publications is 7.021 years.
The average impact factor of the hosting journals is 33.119.
The average percentage of self-citations in the reference list is 22.188%.
The average percentage of references indexed in Web of Science is 68.711%.

Quotes

"If the impact of research is what Public Research Organizations (PROs) should maximise rather than quality, then why resort to evaluation methods and incentivising systems based on the assessment of quality through peer review of scientific publications?"
"The debate on which of the two approaches is preferable for research evaluation has recently been reignited by the Coalition for Advancing Research Assessment (CoARA) initiative. CoARA advocates that research assessment should be primarily based on qualitative judgment, with peer review playing a central role."

Key Insights Distilled From

The role of non-scientific factors vis-a-vis the quality of publications in determining their scholarly impact

by Giovanni Abr... at arxiv.org 04-09-2024

https://arxiv.org/pdf/2404.05345.pdf

The role of non-scientific factors vis-a-vis the quality of publications in determining their scholarly impact

Deeper Inquiries

How can research evaluation frameworks be redesigned to better capture the multidimensional aspects of research impact, beyond just scholarly impact?

Research evaluation frameworks can be redesigned by incorporating a more comprehensive set of metrics that go beyond just scholarly impact. This can include assessing the societal impact of research, such as contributions to policy-making, industry advancements, or societal well-being. Additionally, frameworks can consider the broader dissemination of research through non-traditional channels like social media, blogs, or public engagement activities. Collaborative and interdisciplinary research efforts can also be emphasized to capture the diverse impacts of research across different fields and sectors. By integrating qualitative assessments alongside quantitative metrics, research evaluation frameworks can provide a more nuanced understanding of research impact.

What are the potential drawbacks or unintended consequences of over-emphasizing non-scientific factors in research evaluation, and how can these be mitigated?

Over-emphasizing non-scientific factors in research evaluation can lead to potential drawbacks and unintended consequences. One major concern is the risk of bias or subjectivity in evaluating these factors, which may not always align with the actual impact of the research. This could result in overlooking high-quality research with significant scholarly impact but fewer non-scientific attributes. Additionally, focusing too much on non-scientific factors may divert attention from the core scientific quality of research outputs, potentially compromising the integrity of the evaluation process.
To mitigate these issues, it is essential to strike a balance between assessing non-scientific factors and maintaining a rigorous evaluation of research quality. Clear guidelines and criteria should be established for evaluating non-scientific attributes to ensure consistency and fairness in the assessment process. Transparency in decision-making and accountability in evaluating these factors can help mitigate biases. Furthermore, continuous monitoring and feedback mechanisms can help identify and address any unintended consequences of over-emphasizing non-scientific factors in research evaluation.

What role can advanced bibliometric techniques, such as network analysis and topic modeling, play in providing a more holistic understanding of the knowledge flows and interdisciplinary connections underlying research impact?

Advanced bibliometric techniques, such as network analysis and topic modeling, can play a crucial role in enhancing our understanding of the knowledge flows and interdisciplinary connections underlying research impact. Network analysis can help visualize and analyze the relationships between researchers, institutions, and publications, providing insights into collaboration patterns and knowledge dissemination pathways. By mapping co-authorship networks and citation networks, researchers can identify key influencers and research clusters within a field.
Topic modeling, on the other hand, can uncover thematic trends and emerging research areas by analyzing the content of publications. By identifying common themes and topics across a body of literature, researchers can gain a deeper understanding of the interdisciplinary connections and knowledge diffusion within and across disciplines. This can facilitate the identification of research gaps, interdisciplinary opportunities, and potential areas for collaboration.
Overall, advanced bibliometric techniques offer powerful tools for researchers and evaluators to explore the complex dynamics of research impact, beyond traditional metrics. By leveraging these techniques, stakeholders can gain a more holistic and nuanced perspective on the multifaceted nature of research impact, leading to more informed decision-making and strategic planning in research evaluation and management.