🇬🇧 🇪🇺 "Our results show that individuals who lacked wealth are less likely to support leaving the EU, explaining why so many Brexit voters were wealthy, in terms of their property wealth."
Green, J. and Pahontu, R.L. (2024) ‘Mind the Gap: Why Wealthy Voters Support Brexit’, British Journal of Political Science, pp. 1–21. doi: https://doi.org/10.1017/S0007123423000728.
🇬🇧 🇪🇺 "Our results show that individuals who lacked wealth are less likely to support leaving the EU, explaining why so many Brexit voters were wealthy, in terms of their property wealth."
Green, J. and Pahontu, R.L. (2024) ‘Mind the Gap: Why Wealthy Voters Support Brexit’, British Journal of Political Science, pp. 1–21. doi: https://doi.org/10.1017/S0007123423000728.
"Even though it was hoped that machines might overcome human bias, this assumption often fails due to a problematic or theoretically implausible selection of variables that are fed into the model and because of small size, low representativeness, and presence of bias in the training data [5.]."
Suchotzki, K. and Gamer, M. (2024) 'Detecting deception with artificial intelligence: promises and perils,' Trends in Cognitive Sciences [Preprint]. https://doi.org/10.1016/j.tics.2024.04.002.
"While ChatGPT-4 correlates closely with established risk stratification tools regarding mean scores, its inconsistency when presented with identical patient data on separate occasions raises concerns about its reliability."
Heston TF, Lewis LM (2024) ChatGPT provides inconsistent risk-stratification of patients with atraumatic chest pain. PLOS ONE 19(4): e0301854. https://doi.org/10.1371/journal.pone.0301854