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Träfflista för sökning "WFRF:(Ferreira Rafael) ;hsvcat:5"

Sökning: WFRF:(Ferreira Rafael) > Samhällsvetenskap

  • Resultat 1-4 av 4
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1.
  • Kehoe, Laura, et al. (författare)
  • Make EU trade with Brazil sustainable
  • 2019
  • Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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2.
  • Jones, Benedict C, et al. (författare)
  • To which world regions does the valence-dominance model of social perception apply?
  • 2021
  • Ingår i: Nature Human Behaviour. - : Springer Science and Business Media LLC. - 2397-3374. ; 5:1, s. 159-169
  • Tidskriftsartikel (refereegranskat)abstract
    • Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .
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3.
  • Castro, Mayara Simões de Oliveira, et al. (författare)
  • Understanding peer feedback contributions using natural language processing
  • 2023
  • Ingår i: Responsive and sustainable educational futures. - : Springer Nature. ; , s. 399-414
  • Konferensbidrag (refereegranskat)abstract
    • Peer feedback has been widely used in computer-supported collaborative learning (CSCL) setting to improve students’ engagement with massive courses. Although the peer feedback process increases students’ self-regulatory practice, metacognition, and academic achievement, instructors need to go through large amounts of feedback text data which is much more time-consuming. To address this challenge, the present study proposes an automated content analysis approach to identify relevant categories in peer feedback based on traditional and sequence-based classifiers using TF-IDF and content-independent features. We use a data set from an extensive course (N = 231 students) in the setting of engineering higher education. In particular, a total of 2,444 peer feedback messages were analyzed. The CRF classification model based on the TF-IDF features achieved the best performance. The results illustrate that the ability to scale up the automatic analysis of peer feedback provides new opportunities for student-improved learning and improved teacher support in higher education at scale.
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4.
  • De Rezende, Rafael B., et al. (författare)
  • Modeling and forecasting the yield curve by an extended Nelson-Siegel class of models : A quantile autoregression approach
  • 2013
  • Ingår i: Journal of Forecasting. - : John Wiley & Sons. - 0277-6693 .- 1099-131X. ; 32:2, s. 111-123
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper compares the in-sample fitting and the out-of-sample forecasting performances of four distinct Nelson-Siegel class models: Nelson-Siegel, Bliss, Svensson, and a five-factor model we propose in order to enhance the fitting flexibility. The introduction of the fifth factor resulted in superior adjustment to the data. For the forecasting exercise the paper contrasts the performances of the term structure models in association with the following econometric methods: quantile autoregression evaluated at the median, VAR, AR, and a random walk. As a pattern, the quantile procedure delivered the best results for longer forecasting horizons. 
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