Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights t...Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.展开更多
The Editor welcomes submissions for possible publication in the Letters to the Editor section.Letters commenting on an article published in the Journal or other interesting pieces will be considered if they are receiv...The Editor welcomes submissions for possible publication in the Letters to the Editor section.Letters commenting on an article published in the Journal or other interesting pieces will be considered if they are received within 6 weeks of the time the article was published.展开更多
To the Editor:We read with great interest the recent paper by Baran and colleagues,[1]published in the journal of Hepatobiliary Pancreatic Diseases International.The authors presented nails abnormalities in a 65-year-...To the Editor:We read with great interest the recent paper by Baran and colleagues,[1]published in the journal of Hepatobiliary Pancreatic Diseases International.The authors presented nails abnormalities in a 65-year-old woman with cryptogenic cirrhosis and hepatocellular carcinoma and described them as Terry’s nails.Whether they were Terry’s nails remains controversial,at least far away from展开更多
Within multicellular plants, cells constantly communicate with their neighbors and even distant cells. A cell may produce chemical signals, such as peptides and small molecules, and perceive chemical signals from othe...Within multicellular plants, cells constantly communicate with their neighbors and even distant cells. A cell may produce chemical signals, such as peptides and small molecules, and perceive chemical signals from other cells. Thus, signaling chemicals mediate the exchange of information between cells. There is a simpler and faster way for cells to communicate, i.e., a cell can mechanically nudge its neighbors to send a signal. However, mechanical force is often ignored by biologists, partially due to the difficulty in directly visualizing the force, in contrast to visual detection of signaling molecules.展开更多
Aims Observer error is an unavoidable aspect of vegetation surveys involving human observers.We quantified four components of interobserver error associated with long-term monitoring of prairie vegetation:overlooking ...Aims Observer error is an unavoidable aspect of vegetation surveys involving human observers.We quantified four components of interobserver error associated with long-term monitoring of prairie vegetation:overlooking error,misidentification error,cautious error and estimation error.We also evaluated the association of plot size with pseudoturnover due to observer error,and how documented pseudochanges in species composition and abundance compared with recorded changes in the vegetation over a 4-year interval.Methods This study was conducted at Tallgrass Prairie National Preserve,Kansas.Monitoring sites contained 10 plots;each plot consisted of a series of four nested frames(0.01,0.1,1 and 10 m^(2)).The herbaceous species present were recorded in each of the nested frames,and foliar cover was visually estimated within seven cover categories at the 10 m^(2)spatial scale only.Three hundred total plots(30 sites)were surveyed,and 28 plots selected at random were resurveyed to assess observer error.Four surveyors worked in teams of two.Important Findings At the 10 m^(2)spatial scale,pseudoturnover resulting from overlooking error averaged 18.6%,compared with 1.4%resulting from misidentification error and 0.6%resulting from cautious error.Pseudoturnover resulting from overlooking error increased as plot size decreased,although relocation error likely played a role.Recorded change in species composition over a 4-year interval(excluding potential misidentification error and cautious error)was 30.7%,which encompassed both pseudoturnover due to overlooking error and actual change.Given a documented overlooking error rate of 18.6%,this suggests the actual change for the 4-year period was only 12.1%.For estimation error,26.2%of the time a different cover class was recorded.Over the 4-year interval,46.9%of all records revealed different cover classes,suggesting that 56%of the records of change in cover between the two time periods were due to observer error.展开更多
基金financially supported by the Ningbo University of Technology New Faculty Research Fundthe 2023 Interdisciplinary Innovation Research Cultivation Program of School of Interdisciplinary Studies,RUCKey Project of the National Social Science Foundation of China(21ATQ008)。
文摘Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.
文摘The Editor welcomes submissions for possible publication in the Letters to the Editor section.Letters commenting on an article published in the Journal or other interesting pieces will be considered if they are received within 6 weeks of the time the article was published.
文摘To the Editor:We read with great interest the recent paper by Baran and colleagues,[1]published in the journal of Hepatobiliary Pancreatic Diseases International.The authors presented nails abnormalities in a 65-year-old woman with cryptogenic cirrhosis and hepatocellular carcinoma and described them as Terry’s nails.Whether they were Terry’s nails remains controversial,at least far away from
基金National Natural Science Foundation of China Grants 31825002, 31430010, 31861143021, and 31861130355aRoyal Society Newt on Advanced Fellowship (award NAF\R1\180125).
文摘Within multicellular plants, cells constantly communicate with their neighbors and even distant cells. A cell may produce chemical signals, such as peptides and small molecules, and perceive chemical signals from other cells. Thus, signaling chemicals mediate the exchange of information between cells. There is a simpler and faster way for cells to communicate, i.e., a cell can mechanically nudge its neighbors to send a signal. However, mechanical force is often ignored by biologists, partially due to the difficulty in directly visualizing the force, in contrast to visual detection of signaling molecules.
基金funded by the National Park Service Inventory and Monitoring Program.
文摘Aims Observer error is an unavoidable aspect of vegetation surveys involving human observers.We quantified four components of interobserver error associated with long-term monitoring of prairie vegetation:overlooking error,misidentification error,cautious error and estimation error.We also evaluated the association of plot size with pseudoturnover due to observer error,and how documented pseudochanges in species composition and abundance compared with recorded changes in the vegetation over a 4-year interval.Methods This study was conducted at Tallgrass Prairie National Preserve,Kansas.Monitoring sites contained 10 plots;each plot consisted of a series of four nested frames(0.01,0.1,1 and 10 m^(2)).The herbaceous species present were recorded in each of the nested frames,and foliar cover was visually estimated within seven cover categories at the 10 m^(2)spatial scale only.Three hundred total plots(30 sites)were surveyed,and 28 plots selected at random were resurveyed to assess observer error.Four surveyors worked in teams of two.Important Findings At the 10 m^(2)spatial scale,pseudoturnover resulting from overlooking error averaged 18.6%,compared with 1.4%resulting from misidentification error and 0.6%resulting from cautious error.Pseudoturnover resulting from overlooking error increased as plot size decreased,although relocation error likely played a role.Recorded change in species composition over a 4-year interval(excluding potential misidentification error and cautious error)was 30.7%,which encompassed both pseudoturnover due to overlooking error and actual change.Given a documented overlooking error rate of 18.6%,this suggests the actual change for the 4-year period was only 12.1%.For estimation error,26.2%of the time a different cover class was recorded.Over the 4-year interval,46.9%of all records revealed different cover classes,suggesting that 56%of the records of change in cover between the two time periods were due to observer error.
