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The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

This paper aims to assess the overall social housing development, point out factors affecting it and propose some policy implications for social housing development.

The research investigated investors, credit institutions and officials involved in social housing development. Bac Ninh province currently has 51 social housing projects that have been and are being implemented. The hypothetical regression model has seven latent variables and is tested by the criteria through the SPSS25.0 software.

There are 29 factors belonging to seven groups affecting housing development. Their impact rates range from 3.47% to 30.25%.

The study has only identified the factors affecting social housing development but has not undertaken an in-depth assessment of its development status and forecast for the future. Therefore, this gap needs to be further studied. The proposed research method could also be applied when researching social housing developments in other countries around the world.

To develop social housing to meet the needs of the real estate market, it is necessary to improve the policies that have the strongest impact first. Then, it is necessary to improve the factors with a smaller impact.

The study proposes policy implications for faster housing development for low-income people that improve their living standards.

To the best of the authors’ knowledge, the paper has studied for the first time social housing development and the factors affecting it. The paper also shows the level of their impact so that priority policies can be applied to each factor.

The goal of this study is to propose and test a model of the effect of the socio-cultural context on the disability inclusion climate of organizations. The model has implications of hiring people with disabilities.

To test the model, we conducted a cross-sectional study across four countries with very different socio-cultural contexts. Data were gathered from 266 managers with hiring responsibilities in Canada, China, Norway and France. Participants responded to an online survey that measured the effect of societal based variables on the disability inclusion climate of organizations.

Results indicated support for the theoretical model, which proposed that the socio-cultural context influenced the disability inclusion climate of organizations through two distinct but related paths; manager’s value orientations and their perception of the legitimacy of legislation regarding people with disabilities.

The vast majority of research regarding employment of people with disabilities has focused on supply side factors that involve characteristics of the people with disabilities. In contrast, this research focuses on the less researched demand side issue of the socio-cultural context. In addition, it responds to the “limited systematic research examining and comparing how country-related factors shape the treatment of persons with disability” (Beatty et al., 2019, p. 122).

The study aims to investigate how pregnant and nursing mothers’ stories have been neglected in writing about gender, security and spaces.

The study chronicles Agogo Traditional Area’s pregnant and nursing mothers’ resistance and survival in this conflicted environment. The author used photo voices in a participatory photography design to give conflict-area women a voice. Interviews and observations supported this. Pregnant and nursing mothers were sampled using the purposive and snowball sampling techniques. The data analysis considered narrative analysis, photographic and inductive approaches.

The findings highlighted how these mothers in vicious settings experienced healthcare access and problems, societal issues including gender dynamics, food insecurity, and emotional and psychological well-being.

The findings in this study expand the socio-cultural narratives of pregnant and nursing mothers in violent spaces.

This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital).

The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain.

Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers.

Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.