A Psychometrics Approach to Entropy
| dc.contributor.author | Machado, Joana | |
| dc.contributor.author | Araújo, Isabel | |
| dc.contributor.author | Dias, Almeida | |
| dc.contributor.author | Ribeiro, Jorge | |
| dc.contributor.author | Vicente, Henrique | |
| dc.contributor.author | Neves, José | |
| dc.contributor.editor | Machado, José | |
| dc.contributor.editor | Peixoto, Hugo | |
| dc.contributor.editor | Sousa, Regina | |
| dc.date.accessioned | 2022-05-11T16:43:15Z | |
| dc.date.available | 2022-05-11T16:43:15Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Today's metrics for women housework work (WHW) operate at a quantitative level, specifically measuring time expended on a task and the totality of tasks women perform, not considering that it is a process that is eminently qualitative in nature. To fill this gap, an innovative framework for representing and thinking about big data or knowledge is presented, borrowing from the field of artificial intelligence the methods and methodologies for problem solving, from logic programming the artifacts to improve practice through theory, and from the laws of thermodynamics the construct of entropy, interpreted as the degree of disorder or unpredictability in a system, a principle that may be used to understand system evolution. Last but not least, it also considers the relationship among the disciplines of psychometrics and psychology or sociology (i.e., how certain psychological and sociological concepts such as cognition, knowledge and personality affect WHW satisfaction). | por |
| dc.identifier.authoremail | joana.machado@algoritmi.uminho.pt | |
| dc.identifier.authoremail | isabel.araujo@ipsn.cespu.pt | |
| dc.identifier.authoremail | a.almeida.dias@gmail.com | |
| dc.identifier.authoremail | jribeiro@estg.ipvc.pt | |
| dc.identifier.authoremail | hvicente@uevora.pt | |
| dc.identifier.authoremail | jneves@di.uminho.pt | |
| dc.identifier.capitulo | 7 | |
| dc.identifier.citation | Machado, J., Araújo, I., Almeida-Dias, A., Ribeiro, J., Vicente, H., & Neves, J., A Psychometrics Approach to Entropy. In J. Machado, H. Peixoto, & R. Sousa, Eds., Big Data Analytics and Artificial Intelligence in the Healthcare Industry, Advances in Medical Technologies and Clinical Practice, pp. 177-191, IGI Global, Hershey, USA, 2022. | por |
| dc.identifier.doi | 10.4018/978-1-7998-9172-7.ch007 | por |
| dc.identifier.isbn | 9781799891727 | |
| dc.identifier.numpag | 15 | |
| dc.identifier.sharewith | REQUIMTE/LAQV | por |
| dc.identifier.uri | https://www.igi-global.com/gateway/chapter/301773 | |
| dc.identifier.uri | http://hdl.handle.net/10174/32069 | |
| dc.language.iso | eng | por |
| dc.publisher | IGI Global | por |
| dc.rights | openAccess | por |
| dc.subject | Women’s Household Work | por |
| dc.subject | Artificial Intelligence | por |
| dc.subject | Psychometrics | por |
| dc.subject | Sociology | por |
| dc.subject | Psychology | por |
| dc.subject | Entropy | por |
| dc.subject | Logic Programming | por |
| dc.subject | Knowledge Representation and Reasoning | por |
| dc.title | A Psychometrics Approach to Entropy | por |
| dc.type | bookPart | por |
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