VictorJuiz/thesis huggingface dataset:
A study on Chinese ethnic minority university students' attitudes toward minority education policies and their sense of national identity

Keywords: RDM
attitudinal research
questionnaires
ethnic minority students
sense of national identity
minority education policy attitudes
RDM2022

In China, research into ethnic minorities' national identity has increased significantly since the development of ethnic group theory. However, most existing research on minorities’ national identity has relied primarily on theoretical studies, with relatively few empirical studies conducted. Aiming to better understand minority students’ perceptions toward relevant educational policies, and the potential association between policy attitudes and their sense of national identity, this study takes an online survey as the data collection method which is philosophically grounded in pragmatist position. Specifically, the questionnaire includes a policy attitude scale, a scale of sense of national identity, and an open-ended question, in which the two scales were adapted from previous research. Findings suggest that the sampled students (n = 119) generally hold positive attitudes towards ethnic minority education policies and have relatively strong sense of national identity. The responses generated from the open-ended questions indicate three major themes: perceived benefits of multilingualism, the diversity of opinions on preferential admission policies, and the perceived importance of preserving minority cultures both within minority groups and in the Chinese mainstream society. This study revealed that gender did not significantly influence policy attitudes or senses of national identity among sampled students, but that students' grade level may have a significant influence on both. Most importantly, findings indicate that students' policy attitude can explain 46.8% of the variance in students' sense of national identity when controlling for their gender. The results triggered multiple policy and practical implications, leading to further considerations of how sense of national identity could be taken into account in the formulation, adjustment, and improvement of minority education policies, and how relevant education policies could help build and enhance ethnic minority university students’ sense of national identity.
Attitudes towards academic dishonesty: Russian and British students 
Keywords: cross-cultural research
Moral judgements
vignette experiment
RDM
cheating
survey
RDM2022
cognitive interviews
back-translation
academic dishonesty

Literature on academic dishonesty has been widespread, but it has been approaching the issue from either the standpoint of morality or convention and plagued by methodological shortcomings. Going beyond previous studies based on Social Domain Theory, a vignette experiment was created to include both students’ perceptions of moral (fairness) and conventional (acceptability) judgements using a one between (Culture) × two within (Stakes and Exposure) factors design, controlling for academic integrity involving students from British (N = 113) and Russian (N = 453) universities. The vignettes were carefully calibrated using cognitive interviews and back-translations to fit both contexts. New findings emerged. First, this study found that perceptions of academic dishonesty involve both moral (fairness) and conventional (acceptability) judgements. Second, these judgements were affected by cultural and, in some instances, contextual factors. Specifically, British students perceived cheating as unfair and unacceptable, while Russian students regarded cheating as unfair but somewhat acceptable. Third, contextual drivers, such as harm perceptions, affected Russian students’ judgements on the fairness and acceptability of academic misconduct, while British students’ judgements were immune to contextual differences. Thus, Russian students had less negative attitudes toward cheating if it did not harm other students, and they condemned whistle-blowing in such cases, referring to a whistle-blower as a “snitch”. Finally, higher academic integrity was associated with lower perceptions of fairness and acceptability. These findings underscore that students’ judgements of academic dishonesty are multifaceted and malleable, urging more nuanced and cross-cultural investigations. On the policy side, they also suggest universities should introduce honour codes and develop courses on academic ethics, which have the potential to decrease the level of academic dishonesty.
A study on the impact of the ‘Double Reduction’ policy on the parenting styles and anxiety levels of parents of Grade 5-6 students in Guangdong, China
Keywords: survey
RDM
thematic analysis
double reduction
interviews
socioeconomic status
parents' anxiety
parenting styles
China
RDM2022
shadow education
educational policy
factor analysis

This research evaluates the double reduction policy impact on parenting styles and anxiety levels of parents of Grade 5-6 students in Guangdong, across different SES groups. The mixed method design is adopted, including thematic analysis, factor analysis and regression analysis. Among different levels, the city acts as an intermediating channel through which the policy impact differs across household characteristics. In tier 1 cities, due to the large education system and the legacy of shadow education, the competition for education resources remains fierce, so parents are more likely to feel anxious and will more commonly rely on intensive parenting, as a response. Outside the tier 1 cities, the double reduction policy has significantly relieved the competition in the education environment. After the external competition pressure is eased, parents are more inclined to return to their intrinsic parenting ideas, and the education anxiety is to some extent reduced.
On kernel and feature learning in neural networks
Keywords: neural networks
feature learning
kernel methods

Inspired by the theory of wide neural networks (NNs), kernel learning and feature learning have recently emerged as two paradigms through which we can understand the complex behaviours of large-scale deep learning systems in practice. In the literature, they are often portrayed as two opposing ends of a dichotomy, both with their own strengths and weaknesses: one, kernel learning, draws connections to well-studied machine learning techniques like kernel methods and Gaussian Processes, whereas the other, feature learning, promises to capture more of the rich, but yet unexplained, properties that are unique to NNs.
In this thesis, we present three works studying properties of NNs that combine insights from both perspectives, highlighting not only their differences but also shared similarities. We start by reviewing relevant literature on the theory of deep learning, with a focus on the study of wide NNs. This provides context for a discussion of kernel and feature learning, and against this backdrop, we proceed to describe our contributions. First, we examine the relationship between ensembles of wide NNs and Bayesian inference using connections from kernel learning to Gaussian Processes, and propose a modification that accounts for missing variance at initialisation in NN functions, resulting in a Bayesian interpretation to our trained deep ensembles. Next, we combine kernel and feature learning to demonstrate the suitability of the feature kernel, i.e. the kernel induced by inner products over final layer NN features, as a target for knowledge distillation, where one seeks to use a powerful teacher model to improve the performance of a weaker student model. Finally, we explore the gap between collapsed and whitened features in self-supervised learning, highlighting the decay rate of eigenvalues in the feature kernel as a key quantity that bridges between this gap and impacts downstream generalisation performance, especially in settings with scarce labelled data. We conclude with a discussion, including limitations and future outlook, of our contributions.
Uneven development and insurgency in Turkey: a computational approach

Keywords: econometrics
deep learning
network science

This thesis develops computational techniques to gather, process, and analyze fine- grained data on the war between the Turkish State and the Partiya Karkeren Kurdistan (PKK), a Kurdish insurgent group. In three chapters, I seek to better understand the reasons that lead people join the PKK, assess the impact of development policies aimed at dissuading them from doing so, and explain the group’s structural resilience to military force. The first chapter explores the recruitment of young urban recruits using web scraping, fuzzy matching, and other computational techniques. Leveraging an unprecedentedly detailed research design, militants are compared to random samples of Turkish citizens. I find evidence linking insurgent recruitment and a range factors including birth order and family size, peer effects, and conflict-induced migration. The second chapter explores economic motivations in Turkey’s agrarian Southeast using remote sensing and spatial econometrics. I find that clashes are more frequent following poor harvests, irrigation decouples agricultural income from rainfall, and that conflict was reduced in areas benefiting from a state-sponsored agricultural development program. The third chapter examines the PKK as a whole, focusing on its structural characteristics. I develop a new methodology that leverages deep learning to create a social network graph based on co-appearance in photographs which retains many of the broad structural features of the PKK. Analytical results indicate that the densely interconnected nature of the PKK makes it highly robust to a range of counterinsurgency strategies. Together, substantive findings suggests that development policy is a far more promising avenue for the resolution of the conflict than military policy, while the methodological contributions include the development of forward looking analytical techniques and open source software that enable highly detailed quantitative analysis of civil conflict.
Stakeholder consultations in national education policy (2020): a qualitative evaluation of consultations in India’s education policyscape

Keywords: good consultation
CIE2022
FFR
evaluation
policy consultations
education policymaking
elite interviews
theory and practice
CIE
policymaking
policy document analysis
negative capability

This qualitative study attempts to evaluate the consultative process of India's National Education Policy (2020). Using a systemic lens, it aims to realise two broad research objectives. Firstly, it attempts to normatively differentiate between consultation theory and practice. Secondly, it aspires to define 'good consultation' and provide a contextual and comprehensive framework for this purpose. The elite interviews of NEP's policy leaders and document analysis of critical consultation policy texts produced three central findings. Firstly, while there is a consensus on the process and outcome goals of consultations across the stakeholders, the evidence demonstrates that it is not systematically measured or understood. Secondly, the consultations only poorly address the puzzle of public involvement. There is little to no empirical evidence of ambitious participation or effective systems. Thirdly, the consultative process is substantially different in theory and implementation. This incongruence has its advantages and disadvantages and can be observed in aspects such as the use of native language, local level participation and the adoption of technology. The policy texts and interview transcriptions were analysed using a reflexive thematic and content analysis processes, respectively. This analysis was founded on a relativist philosophy and performed through a social constructivist approach. Two insights emerged from the study and have a potential role in improving future consultative practices. First, consultations are normatively valuable and possess a negative capability to reform the education policyscape. Second, although it is evident that the critique of consultations is too perfunctory, the study concludes that it is crucial to ground policy rhetoric on policy reality to avoid such misconceptions.
'But if you can't rape your wife, who can you rape?' toward a course-of-conduct offence centring partner sexual coercion in Canada
Keywords: coercive control
sexual violence
sexual coercion
criminal law
domestic violence
Canada
violence against women
Canadian law
partner sexual violence
sexual assault

Despite the removal of the marital exemption to rape 40 years ago in Canada, the law still fails to treat partner sexual assault on par with other sexual assaults. Starting from the norm of stranger rape, it struggles to make sense of partner sexual violence in a culture that normalizes sexually coercive behaviours. Because partner sexual violence presents a serious empirical, social, and legal problem, it deserves to receive primary consideration and should not be treated by legal scholars as a mere exception to the stranger rape model. This process of ‘centring’ partner sexual violence enables me to identify a gap in the law and propose new avenues to address chronic and non-physically forced sexual violence.
Noting that the stranger rape model presupposes a unique interaction between victim and offender, I work by analogy with coercive control to criticize the ‘incident model’ of sexual assault. I work ‘bottom-up’ from the empirical reality of partner sexual violence to propose creating course-of-conduct provisions criminalizing repeatedly engaging in pre-defined acts of sexual coercion. Developing criminal provisions that are behaviourally specific and that do not require proving non-consent (among other features) produces a strategy that could pre-empt the implementation problems that plague the legal response to partner sexual violence.
Beyond its exploration of concrete legal reform possibilities, my work contributes to the sexual violence field by focusing on the context of intimate relationships, which is often neglected by legal scholarship. My research confronts the injustices still faced by victims of partner sexual violence and opens up new ways of thinking about legal responses to sexual violations.
Child welfare and the impact of late-nineteenth-century English reformatory and industrial schools: a life-course analysis of social mobility, emigration, and character
Keywords: poverty
children
emigration
reformatory
industrial school
delinquent
life course analysis
social mobility
Canada
nineteenth century
welfare
empire
philanthropy
delinquency
domestic service

This thesis fundamentally reshapes understandings of working-class life and social mobility in modern Britain and disrupts existing histories of nineteenth-century institutional welfare. Focusing on the lives of 230 children who entered two Surrey-based reformatory and industrial schools between 1850 and 1895, it integrates qualitative and quantitative analysis. It uses rich archival data together with the latest digitised sources to contextualise children’s lives with those of their families (c. 1200 individuals). It reveals children’s experiences of welfare across the life course, within and beyond the British Isles.
The thesis explores the intellectual origins of reformatory and industrial schools. Through a focus on the causes of family breakdown, it reveals the harmful backgrounds of many children and shows that a substantial proportion considered institutional care preferable to life at home. It builds on these new understandings to argue for a reassessment of the purpose and effectiveness of institutional welfare.
The study provides the first comparative study of children’s life courses and demonstrates that philanthropic intervention delivered gains in social mobility for girls and especially boys. This contradicts existing characterisations of nineteenth-century welfare as ineffective or driven by motives of class control. Through an examination of the motives behind emigration, it shows that children were active agents in this process as they sought financial opportunity overseas. This argues for the inclusion of juvenile emigrants in histories of empire. It shows that working-class families thought of opportunity as transnational but not necessarily imperial.
The examination of children’s pre-institutional lives together with the social mobility benefits that welfare delivered, shows that nineteenth-century institutional care offered advantages unmatched in the twentieth century when welfare became centralised, living standards rose and investment dropped. This transforms existing histories of working-class life and undermines conventional narratives of linear progress in the welfare state.
Predictive models of metabolite concentration for organoid expansion
Keywords: mass transport
homogenisation
reduced-order model
fluid flow
bioreactor
multiscale
asymptotic
organoid culture

This thesis is motivated by the culture of organoids, specifically developing mathematical models for metabolite transport and organoid growth within a fed-plate bioreactor. The bioreactor of interest is the proprietary CXP1 bioreactor, invented by biotechnology company Cellesce, which consists of a layer of hydrogel over which culture media is flowed. Organoids are embedded within the hydrogel and flow is thought to enhance nutrient delivery to, and facilitate waste removal from, the organoids. A key priority is ensuring uniformity in organoid size and reproducibility; qualities that depends on bioreactor design and operating conditions. We show how mathematical modelling can be used to improve the yield of organoids grown within CXP1, by predicting metabolite concentrations during culture for different operating conditions.
In this thesis, we develop a series of models focused on different spatial scales and aspects of organoid growth and bioreactor operation, including metabolite transport and fluid flow. We exploit the slender bioreactor geometry and use an asymptotic approach to derive a longwave approximation of the transport problem within a 2D representation of CXP1, where the organoids are modelled via volumetric (bulk) reaction terms. We show these reduced models are excellent approximations to the full 2D model and explore the behaviour of the longwave approximation using both analytical and numerical approaches.We then develop a model for growth of individual organoids embedded within the hydrogel, modelling the organoids as spheres with temporally and spatially varying radii within a cubic lattice. Hence, we derive, via a homogenisation approach, the effective macroscale behaviour across the organoid-hydrogel region while also retaining the relevant organoid-scale information. Next, we consider the corresponding 3D flow problem. We exploit the slow nature of the flow and the geometry of the media domain, and systematically reduce the problem using a lubrication scaling to a 2D streamfunction problem of a circle with a point source and point sink. Finally, we combine the 3D flow model into the model for metabolite transport and organoid growth. We perform an asymptotic analysis on this model to reduce its spatial dimension --- this allows us to efficiently predict the metabolic environment and associated organoid size across the CXP1 bioreactor.
Understanding the role of C16orf72 in the DNA replication stress response
Keywords: PARP
DNA replication stress response
C16orf72
PARPs
DDR
replication stress
poly(ADP-ribose) polymerases
DNA damage response
synthetic lethality

The human genome continually undergoes DNA damage that is endogenous and exogenous in origin. To protect the genome from this DNA damage, cells have evolved a plethora of signalling pathways, known as the DNA damage response (DDR). The poly(ADP-ribose) polymerase (PARP) enzyme family can regulate a variety of DDR pathways by modifying substrates with ADP-ribose, a type of chemical post-translational modification. However, our understanding of these pathways, and the factors involved in them, remains in their infancy. Chemical inhibitors of PARPs (PARPi) have emerged as key therapeutic tools to combat human diseases, thereby underlining the importance of understanding the pathways controlled by this enzyme family.
To investigate whether additional PARP enzymes might function in the absence of PARP1 and PARP2 in response to DNA damage, a genetic approach using a small-scale siRNA screen was taken. From this, I found that loss of PARP6 or PARP14 may rescue the PARPi-induced further sensitisation of PARP1/PARP2 knockout cells to methyl methanesulfonate (MMS). This suggests that PARP6 or PARP14 may be trapped to DNA by olaparib and supports the notion that either of these PARPs may participate in the repair of MMS-induced DNA damage in the absence of PARP1 and PARP2.
To reveal novel DDR proteins that are synthetic lethal with the combined loss of PARP1 and PARP2, a genome-wide CRISPR dropout screen was performed. From this, I identified the poorly characterised protein C16orf72 as being synthetic lethal with the combined loss of PARP1 and PARP2. Genetic deletion of C16orf72 sensitises cells to the DNA replication stress-inducing agents, hydroxyurea (HU) and aphidicolin (APH) indicating a function for C16orf72 in the DDR pathways that respond to DNA damage induced by these agents. Indeed, I find that C16orf72 is recruited to chromatin in response to exogenous replication stress, thereby localising it to damaged chromatin. In addition, I find that C16orf72 is required to limit replication catastrophe under conditions of prolonged replication stress. Together, these findings suggest that C16orf72 is a novel DDR factor that functions in response to DNA replication stress.
Collectively, my findings represent two major advances. Firstly, I identify PARP6 or PARP14 as novel PARP family members that may participate in the repair of MMS-induced DNA damage in the absence of PARP1 and PARP2. Secondly, I identify C16orf72 as a novel component of the DDR and show that it functions in response to DNA replication stress. Taken together, my findings expand our understanding of two important aspects of the DDR: ADP-ribosylation signalling and the DNA replication stress response.
Leveraging genome wide association studies and single cell RNA sequencing in inflammatory bowel disease
Keywords: single cell RNA sequencing
enrichment testing
scRNA-seq
Crohn’s disease
ulcerative colitis
inflammatory bowel disease
GWAS
IBD
CD
genome-wide association studies
UC

In this thesis, the main scientific pursuit is that of leveraging information from genome-wide association studies (GWAS) in combination with gene expression datasets such as to narrow down the list of genes and cell-types that may be important for pharmacological targeting in heritable traits, particularly for inflammatory bowel disease (IBD). I will introduce this class of diseases and their particular manifestations, as well as the known environmental and genetic risk factors. Then, I will offer a brief review of the methods which have been used so far to highlight causal genes, pathways and cell-types using GWAS data. More focus is given towards the methods which use functional genomics data to augment the mechanism-seeking for GWAS hits. In chapter 2, I show through simulation that different genetic enrichment-testing methods can perform better than others depending on the architectural context. I also develop a novel meta-analysis technique which retains the best statistical power regardless of the particular genetic scenario being tested. I then apply these methods to datasets relevant for IBD research and identify actionable evidence, including cell-states and drugs that are likely to be important – as well as raising more questions about the complex aetiology of IBD. I dive into the difficulties and advantages of using single-cell gene expression data for these purposes, together with simulations to assess the precision of such investigations. Last but not least, the thesis showcases a novel RNA and chromatin accessibility dataset investigating the functions of different costimulations in T-cells. I then detail how this data helps us to interpret the functions of several GWAS risk variants in IBD and potentially other heritable immune traits.