Integrating regression and multiobjective optimization techniques to analyze scientific perception
Abstract Science holds high prestige in society and understanding public perception of what is considered scientific is essential. The scientificity of a profession is the degree of scientific legitimacy and is determined by the quality of its scientific procedures. Higher levels of scientificity ar...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-89065-2 |
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| author | Sandra González-Gallardo María Isabel Sánchez-Rodríguez Ana B. Ruiz Mariano Luque |
| author_facet | Sandra González-Gallardo María Isabel Sánchez-Rodríguez Ana B. Ruiz Mariano Luque |
| author_sort | Sandra González-Gallardo |
| collection | DOAJ |
| description | Abstract Science holds high prestige in society and understanding public perception of what is considered scientific is essential. The scientificity of a profession is the degree of scientific legitimacy and is determined by the quality of its scientific procedures. Higher levels of scientificity are achieved when scientific results are more objective, impartial, and neutral. In this work, we first estimate the scientificity levels attributed to various professions using a logistic regression model. Then, we explore ways to simultaneously improve their scientific perception by means of multiobjective optimization techniques. To this aim, the statistical results are used to formulate a multiobjective optimization model that maximizes the scientific perception of all the professions considered. The findings provide insights into science policy measures to optimize resource allocation in order to increase the scientific perception of the professions. |
| format | Article |
| id | doaj-art-21444fac72e4431187b89089488760e8 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-21444fac72e4431187b89089488760e82025-02-09T12:32:15ZengNature PortfolioScientific Reports2045-23222025-02-0115111610.1038/s41598-025-89065-2Integrating regression and multiobjective optimization techniques to analyze scientific perceptionSandra González-Gallardo0María Isabel Sánchez-Rodríguez1Ana B. Ruiz2Mariano Luque3Department of Applied Economics (Mathematics), Universidad de MálagaDepartment of Statistics and Business, Faculty of Law and Business, University of CórdobaDepartment of Applied Economics (Mathematics), Universidad de MálagaDepartment of Applied Economics (Mathematics), Universidad de MálagaAbstract Science holds high prestige in society and understanding public perception of what is considered scientific is essential. The scientificity of a profession is the degree of scientific legitimacy and is determined by the quality of its scientific procedures. Higher levels of scientificity are achieved when scientific results are more objective, impartial, and neutral. In this work, we first estimate the scientificity levels attributed to various professions using a logistic regression model. Then, we explore ways to simultaneously improve their scientific perception by means of multiobjective optimization techniques. To this aim, the statistical results are used to formulate a multiobjective optimization model that maximizes the scientific perception of all the professions considered. The findings provide insights into science policy measures to optimize resource allocation in order to increase the scientific perception of the professions.https://doi.org/10.1038/s41598-025-89065-2Scientific perceptionScience policyLogistic regressionMultiple criteria decision making |
| spellingShingle | Sandra González-Gallardo María Isabel Sánchez-Rodríguez Ana B. Ruiz Mariano Luque Integrating regression and multiobjective optimization techniques to analyze scientific perception Scientific Reports Scientific perception Science policy Logistic regression Multiple criteria decision making |
| title | Integrating regression and multiobjective optimization techniques to analyze scientific perception |
| title_full | Integrating regression and multiobjective optimization techniques to analyze scientific perception |
| title_fullStr | Integrating regression and multiobjective optimization techniques to analyze scientific perception |
| title_full_unstemmed | Integrating regression and multiobjective optimization techniques to analyze scientific perception |
| title_short | Integrating regression and multiobjective optimization techniques to analyze scientific perception |
| title_sort | integrating regression and multiobjective optimization techniques to analyze scientific perception |
| topic | Scientific perception Science policy Logistic regression Multiple criteria decision making |
| url | https://doi.org/10.1038/s41598-025-89065-2 |
| work_keys_str_mv | AT sandragonzalezgallardo integratingregressionandmultiobjectiveoptimizationtechniquestoanalyzescientificperception AT mariaisabelsanchezrodriguez integratingregressionandmultiobjectiveoptimizationtechniquestoanalyzescientificperception AT anabruiz integratingregressionandmultiobjectiveoptimizationtechniquestoanalyzescientificperception AT marianoluque integratingregressionandmultiobjectiveoptimizationtechniquestoanalyzescientificperception |