Human rights protection under the ICCPR: when can and should States derogate? A critical analysis in the context of New Zealand's COVID-19 response

Public emergencies like global pandemics subject human rights to extraordinary vulnerability. The International Covenant on Civil and Political Rights (ICCPR) permits States to restrict rights by enacting permissible limitations on them at any time and by derogating from their protection in emergencies. This article argues that States should rely on the ICCPR's permissible limitations provisions rather than lodge formal derogations in times of crisis, unlike what many States have done during the COVID-19 pandemic. It draws upon New Zealand's highly successful public health response to support this proposition. The article argues that the accountability machinery for compliance with States' rights obligations is stronger when permissible limitations are enacted. Where States do rely on the right to derogate, the article suggests some improvements to existing international accountability mechanisms. These include enhancing the analysis to be contained in notices of derogation and advance capacity-building to enable States to better decide if derogation is necessary in the first place. Ultimately, the article argues that keeping States within the international human rights system is ideal. This can be achieved through reliance on the flexibility built into the ICCPR via its permissible limitations provisions rather than its right of derogation. [ FROM AUTHOR] Copyright of International Journal of Human Rights is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Exploring the relationship between exposure to COVID-19 and donations during the COVID-19 pandemic: The mediating roles of emotions and risk perception.

Objective: Public emergency events like the COVID-19 pandemic are special occasions that need immediate massive funding from public donations. Thus, understanding the determinants of donation behaviors under public emergencies is important for both researchers and practitioners. This study investigated the effect of personal and local exposure to incidences of COVID-19 on donation behaviors. Specifically, we examined the mediating effects of risk perception and emotions on the relationship between exposure to COVID-19 and donation behaviors. Methods: The data were from a survey distributed in China between March 20 and 30th, 2020. Participants' donation choice at the end of the survey was used to measure their donation behaviors. Participants' emotions, risk perception, and personal exposure were assessed in the questionnaire. Local exposure was the 30-day confirmed cases obtained from the National Health Commission of the People's Republic of China. A total of 8,720 participants (Mean age = 28.91, 43.6% females) completed the online survey. Results: Based on the results from the mediation analysis, we found that people with stronger positive and negative emotions, higher risk perception, and more personal exposure to COVID-19 were more likely to donate. Furthermore, the effects of both personal and local exposure on donations are mediated by risk perception and negative emotion. Both higher personal and local exposure led to stronger negative emotions and higher risk perception, which in turn led to more donation behaviors. Discussion: This study extends our knowledge of donation behaviors during public emergencies. Our results suggest that policymakers and charity organizations should elicit stronger emotions and risk perception by exposing the severity of the disaster in advertisements to promote donations.

The predicting public sentiment evolution on public emergencies under deep learning and internet of things

With the Internet's rapid development and the increasing amount of netizens, social contradictions frequently manifest over the Internet. Public emergencies develop and spread constantly online. Thus, it is of great significance to reasonably address the Online Public Sentiment (OPS) in the current critical stage of social transformation. The aim is to create a safe and credible network environment and realize the modern transformation of the dynamic evolution of OPS in public emergencies. Firstly, this paper expounds on the blocking process of the OPS evolution on public emergencies according to the Internet of Things-native big data. Then, it discusses the algorithm process of the Long Short-Term Memory (LSTM) Neural Network (NN) model. Further, it optimizes the LSTM NN model using the Adaptive Momentum Estimation (Adam). Finally, it simulates and predicts the OPS evolution using Artificial Intelligence technology and big data. The results show that the Adam-optimized LSTM NN model can predict the hotness of OPS in the dynamic evolution with high prediction accuracy. In predicting OPS evolution, the Mean Relative Errors (MRE) of the proposed Adam-LSTM, LSTM, and Backpropagation NN models are 0.06, 0.10, and 0.14, respectively. The proposed Adam-LSTM model presents the least MRE on the hotness of OPS. The relevant governments can refer to model-predicted OPS evolution to control public emergencies and OPS through the IoT. Therefore, the proposed Adam-LSTM model is feasible for predicting the OPS hotness. The finding has particular research significance for employing the LSTM model under the IoT in predicting the OPS evolution in public emergencies. Lastly, the OPS on public emergencies can be effectively guided thanks to the proposed Adam-LSTM prediction model and time nodes.

The Impact of Price Support Policies and Public Emergencies on Agricultural Futures Markets - A Multifractal Cross-Correlations Analysis between China and the US

This paper investigates the presence and asymmetry of cross-correlations between agricultural futures markets in China and the US as well as the impact of price support policies and public emergencies (Sino-US trade conflict and COVID-19 pandemic) on the cross-correlations by the multifractal methods. The results show that the fluctuation characteristics and conduction directions of cross-correlations are asymmetric. The price fluctuations of soybean and corn futures in China are easier to be affected by the US soybean and corn futures. We find that the cross-correlations are multifractal under different price support policies and pubic emergencies. The price support policies with greater interventions on soybean and corn prices have aggravated the complexity of cross-correlations between the two futures markets in China and the US. The soybean and corn futures in China are hardly correlated to the US futures under the dual effect of the Sino-US trade conflict and the COVID-19 pandemic. The Sino-US trade conflict strengthens the complexity of cross-correlation for soybean futures and weakens it for corn futures, while the COVID-19 pandemic enhances the complexity of cross-correlations for soybean and corn futures. In addition, the fat-tailed probability distributions in different price support policy and public emergency periods have a dominant influence on the multifractality of cross-correlations. © 2022 World Scientific Publishing Company.

Financial Risk Prediction Based on Stochastic Block and Cox Proportional Hazards Models

Since 2019, the sudden outbreak of COVID-19 has made huge impacts on various aspects of society, especially the financial industries that are closely related to the national economy and people’s livelihood. Finance is a data-intensive field and its traditional research models include supervised and unsupervised models, state-based models, econometric models, and stochastic models. However, the above models are prone to lose their effectiveness in the situation of an extremely complex financial ecosystem with a large number of nonlinear unpredictable effects, such as those caused by COVID-19. To address this issue, we comprehensively explore and fuse Stochastic Block Model (SBM) and Cox Proportional Hazards Model (COX) for a reliable and accurate financial risk prediction. Specifically, SBM, which is popular in social network analysis, is employed to capture the impact factors on the financial industry in public emergencies, and COX is then leveraged to determine the duration of the impact factors. An extensive experimental evaluation validates the effectiveness of our framework in predicting financial risk. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Human rights protection under the ICCPR: when can and should States derogate? A critical analysis in the context of New Zealand’s COVID-19 response

Public emergencies like global pandemics subject human rights to extraordinary vulnerability. The International Covenant on Civil and Political Rights (ICCPR) permits States to restrict rights by enacting permissible limitations on them at any time and by derogating from their protection in emergencies. This article argues that States should rely on the ICCPR’s permissible limitations provisions rather than lodge formal derogations in times of crisis, unlike what many States have done during the COVID-19 pandemic. It draws upon New Zealand’s highly successful public health response to support this proposition. The article argues that the accountability machinery for compliance with States’ rights obligations is stronger when permissible limitations are enacted. Where States do rely on the right to derogate, the article suggests some improvements to existing international accountability mechanisms. These include enhancing the analysis to be contained in notices of derogation and advance capacity-building to enable States to better decide if derogation is necessary in the first place. Ultimately, the article argues that keeping States within the international human rights system is ideal. This can be achieved through reliance on the flexibility built into the ICCPR via its permissible limitations provisions rather than its right of derogation. [ FROM AUTHOR] Copyright of International Journal of Human Rights is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Buying to Cope With Scarcity During Public Emergencies: A Serial Mediation Model Based on Cognition-Affect Theory.

Panic buying is a common phenomenon that occurs during public emergencies and has a significant undesirable impact on society. This research explored the effect of scarcity on panic buying and the role of perceived control and panic in this effect through big data, an online survey and behavior experiments in a real public emergency (i.e., COVID-19) and simulative public emergencies. The findings showed that scarcity aggravates panic buying (Studies 1-3), and this aggravation effect is serially mediated by perceived control and panic (Studies 2-3). Moreover, this serial mediation model is more suitable for public health emergencies (Study 3). These findings enrich the understanding of panic buying and provide important enlightenment for guiding rational public behavior and managing public opinion during public emergencies.

Analysing the impact of smart city service quality on citizen engagement in a public emergency.

The outbreak of novel coronavirus disease 2019 (COVID-19) has brought great challenges to the improvement of global smart city services. To date, few studies have been conducted on the effects of service quality on citizen engagement in smart cities in a public emergency. Based on the stimulus-organism-response (SOR) model and uncertain management theory, this study analyses the impact of the service quality of smart city system on citizen engagement in a public emergency. Data were collected in Chinese smart cities. Three valuable and novel results are identified. First, high-quality information content, highly reliable systems and highly responsive systems have a significant positive effect on citizens' continuous experiences, but not on citizens' immediate experiences. Second, both the immediate and continuous experiences of citizens have a significant positive effect on citizen engagement. Third, continuous experiences impose a full mediation effect between information content and citizen engagement, between reliability and citizen engagement and between responsiveness and citizen engagement. As its main contribution, this study focuses on the construction of a theoretical model. Based on this model, smart city managers can understand citizens' reactions in public emergencies from stimulation to experience and their behaviours in relation to smart city services.

Cross-cultural adaptation, validity, and reliability of the Chinese version of the Nurses' Perceptions of Disaster Core Competencies Scale (NPDCC).

BACKGROUND: In recent years, disasters occurred frequently all over the world, and the role of nurses in public health emergencies and disaster emergencies was highlighted under the background of the covid19 epidemic. However, there was a lack of education and evaluation. Our study aims to cross-cultural adapt the Nurses' Perceptions of Disaster Core Competencies Scale (NPDCC) and evaluate the reliability and validity of the Chinese version. METHODS: We translated the scale following the translation-integration-back translation-expert review procedure, adapted according to Chinese culture. We evaluated the reliability and validity of the scale, and a total sample of 911 nurse data from the Yangtze River Delta Regional Nursing Alliance Hospital was gathered. RESULTS: The Chinese version of NPDCC included 45 items, 5 factors (critical thinking skills, special diagnostic skills, general diagnostic skills, technical skills, and communication skills) were extracted from the analysis, which could explain the 68.289% of the total variance. The content validity index was 0.925. The Cronbach's α of the total NPDCC score was 0.978, and 0.884-0.945 for every factor. The split-half for the scale was 0.930, and every factor was 0.861-0.894. CONCLUSIONS: The Chinese version of NPDCC has excellent reliability and validity, and it is suitable to measure nurses' perceptions of disaster core competencies in China. The next step is to promote the application in a large scale.

Suggestions on surgical treatment during coronavirus disease 2019 (COVID-19) pandemic.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 virus, is now generating a global epidemic, leading to a severe public health emergency. Until April 12, 2020 around 1,700,954 confirmed cases and 105,633 deaths have been reported all over the world. The World Health Organization (WHO) has declared COVID-19 as a Public Health Emergency of International Concern. Under this circumstance, surgical activities should be carefully evaluated to avoid excessive occupation of limited medical resources, and to reduce the possibility of hospital infection. China has achieved an inspiring achievement on epidemic control. Here, we reviewed available studies on surgical activities during the outbreak, in combination with our current experience, with the aim of providing feasible suggestions on surgical issues during the COVID-19 pandemic.