VictorJuiz/thesis huggingface dataset:
Walls and gates: Jewish ghettos and the built environment in Ferrara, Florence, and Modena (c. 17-50-1840)

This thesis analyses how management of the urban landscape influenced interactions between Italian Jews and Catholics in Ferrara, Florence, and Modena from the creation of the ghettos to the 1840s. I argue that the physical location of the ghettos at the heart of these cities demanded inclusion within the urban community through bureaucratic actions, a process I call embeddedment. Drawing upon Edward Soja's notion of the socio-spatial dialectic, in conjunction with social identity theory, I take a comparative approach which highlights broader patterns of convergence and divergence Italy since these three case studies illuminate practices under three different political regimes: the theocratic Papal States, the Habsburg Empire, and the Este dynasty. In all three cases, this thesis demonstrates that embeddedment, rather than the standard tropes of inclusion and exclusion, defined Italian Jewish experience during the era of the ghettos.
Using a longue durée approach, Part One explores the legal foundations for Jewish presence in Italy (Chapter 1), the creation of the ghettos in these cities (Chapter 2) and the historical evolution of the primary institutional actors – the Inquisition, the Italian health boards, and Jewish leadership (Chapter 3). Part Two proceeds topically and chronologically through the late–eighteenth and early–nineteenth centuries. Chapter 4 focuses on the policies for ritual slaughter and burial of the dead in all three cities. The issue of lunacy in Enlightenment Florence is discussed in chapter 5. Chapter 6 explores conversion through the lens of a civil marriage petition in Modena during the first emancipation under Napoleon. Chapter 7 focuses on the Restoration era through analysis of the arrest of five Christian men who entered the ghetto of Ferrara on the Sabbath. Chapter 8 considers fire management the impact of epidemic cholera in these cities and their ghettos.

Keywords: ghettos
fire prevention and management
cholera
ritual slaughter
Church and the Jews
Christians
burial and cemetery
conversion
Italian Jews
epidemic disease
civil marriage
insanity
Advisor: Green, A
Earth in focus: the complex sculptures of land art and their 'big picture' effect, as seen through the lens of photography and film (1960s - 1970s)

This dissertation focuses on previously unstudied material of the films and photographs of Land Art – or Earth Art, as it is sometimes interchangeably called – in which the reciprocal relation between the Land Art sculptures in situ (earthworks) and lens-based media is considered. It introduces the notion of ‘complex sculptures’, sculptures that are not only site-specific, located within the landscape or in an exhibition space, but also time-specific, mediated through photography, film, and even television. The complex sculptures of Land Art are thus shown to incorporate both a mediated and phenomenological viewpoint.
I present new archival material to re-evaluate Land Art, especially given the abundant use of lens-based media by the artists of early Land Art, which is linked to the socio-political circumstances of the late 1960s and early 1970s. The importance of a decentring dynamic in the Land artworks is pointed out and related to the ‘primary humility’ that certain critics perceived in Land Art. Not in the sense of a sublime experience that overwhelms reason completely, or as a ‘back to nature’ experience, but through a channelled experience of multiple, constellational elements. It is thus shown that the artists of Land Art were seeking ways in which both presence and absence, ‘presentness’ and distance, would become components of their aesthetics through their search for a continuous relationship between their artworks on-site and the distancing and displacing functions of different media, like film, photography and television. This dialectical constellation of elements is directly bound to the ontology of Land Art (or: its ‘conditions of possibility’), an ontology that points to a search for a different worldview: one that is interested in ‘the bigger picture’ of the relation of human beings to our planet, as well as in a growing awareness – through lived experience – of the intrinsic reciprocity of our lives.

Keywords: complex sculptures
Marinus Boezem
Dennis Oppenheim
sculpture
contemporary art
ontology
Earth art
photography
eco art
Mary Kelly
film
Barry Flanagan
Bildwissenschaft
Walter De Maria
Robert Smithson
land art
aesthetics
phenomenology
Nancy Holt
Michael Heizer
Jan Dibbets
Earthworks
history of art
image theory
postmodernism
Advisor: Johnson, G
Gardner, A
Trait-based community and invasion ecology of terrestrial arthropods

The search for general rules that predict the form, function and fate of biodiversity is an enduring goal in Ecology. Traits which impact the interactions and fitness of organisms have emerged as useful common currency with which to formulate general and predictive rules about ecological processes. A trait-based framework of community assembly will help to elucidate how ubiquitous processes such as interspecific competition shape and maintain biodiversity, and to predict the impacts of environmental change such as invasions by non-native species. Advances in both areas are needed to explain and address recent widespread changes in the diversity of terrestrial arthropods, organisms representing a massive and functionally significant portion of life on Earth.
In this thesis I first review the burgeoning field of terrestrial arthropod trait-based ecology (Chapter 2). Studying ant assemblages in subtropical Asia, I then use trait-based approaches to investigate the mechanistic causes and functional consequences of assembly processes such as interspecific competition, within the context of invasions by non-native species. I find that invasion leads to a functional homogenization across the landscape which, notably, is unmet by comparable changes in taxonomic diversity (Chapter 3). To investigate underlying processes, I test whether differences in ant species’ morphological traits predict their fine-scale spatial associations in ways consistent with theories on interspecific competition (Chapter 4). At the assemblage level, I then show that two opposing mechanisms of competitive exclusion act varyingly on separate morphological, physiological and behavioural traits, causing the invasion to drive contrasting patterns in functional structure (Chapter 5). Addressing a key limitation of trait-based research, I also demonstrate empirically that decisions to exclude intraspecific trait variability from functional diversity assessments can distort the patterns observed, even overturning the conclusions drawn (Chapter 6).
My work strengthens the foundations for a predictive trait-based ecology of animals in general. It makes specific empirical and methodological contributions to the use of traits for understanding community assembly and the competitive mechanisms determining the impacts of invasions on functional diversity. Building on the work described in this thesis, studies investigating how individual and multidimensional traits determine niche and competitive differences between species will further steer Ecology towards general rules for a predictive understanding of biodiversity and associated ecosystem functions.

Advisor: Lewis, O
Guenard, B
Biochemical study of the interactions between cohesin and DNA

Cohesin is a ring like SMC-kleisin complex (S-K ring) that mediates DNA interactions between chromosomes. It is responsible for the phenomenon of sister chromatid cohesion (SCC) and ensures the faithful segregation of chromosomes during mitosis. Cohesin also mediates interactions within chromosomes by organising DNA into loops in both interphase and mitosis. SCC is thought to be mediated by co-entrapment of sister DNAs within a single cohesin S-K ring. Cohesin will also entrap individual chromosomes within its S-K ring during G1, and it is thought this activity is a pre-requisite to cohesion establishment during S phase. To improve our understanding of the mechanism of the entrapment of DNA by S-K rings, I developed a protocol to measure this activity in vitro. By using a cysteine-cysteine crosslinking protocol, I was able to covalently circularise the cohesin ring on DNA and through this create protein-DNA catenations that can resist protein denaturation. This revealed that S-K entrapment was dependent on Scc3 and ATP binding, and was stimulated by Scc2 and ATP hydrolysis. I found both Scc2 and Scc3 are DNA binding proteins and discover that this DNA binding activity is essential for cohesin’s ability to entrap DNA within its S-K ring. I then set out to identify where within the cohesin ring DNA was entrapped, and through this managed to identify a novel mode of DNA interaction, whereby DNA becomes entrapped within two compartments created through cohesin binding to ATP. Entrapment within these two compartments was not associated with passage of DNA into S-K rings, and I propose entrapment of this nature may represent the first step in cohesin’s topological association with DNA.

Keywords: Biochemistry
Chromosome biology
Cohesin
Advisor: Nasmyth, K
Identifying optimal pathways of care in the delivery of carotid interventions

Background: Successful carotid endarterectomy (CEA) and carotid artery stenting (CAS) halve long-term stroke risk but are potentially hazardous. Optimising the carotid intervention pathway may reduce harm.
Aims: This thesis used qualitative and quantitative methodologies to identify: hospital-level factors affecting CEA and CAS procedural outcomes; failures in the CEA pathway for improvement; temporal and regional trends in CEA and CAS provision and outcomes; and patient-level factors affecting procedural and long-term outcomes.
Qualitative Methods and Results: A systematic review of 124,958 patients showed that large hospitals, serving large populations, with vascular beds, clinical pathways and Vascular Surgeons performing CEA were associated with improved outcomes. An ethnographic study, involving 1,072 hours of observations of the CEA pathway in symptomatic patients, identified 110 patient safety incidents primarily in documentation, public health awareness and the care-providing environment. A Healthcare Failure Mode and Effect Analysis of 65 organisational failures by 13 stakeholders recommended patient education to improve stroke recognition, increasing resources, implementing technology, standardising care and improving communication to optimise the CEA pathway.
Quantitative Methods and Results: A 16-year analysis of 68,897 English patients in the Hospital Episode Statistics dataset showed that CEA and CAS age-standardised rates reduced since 2011-2012 with regional variation in provision. Despite temporal improvements in most CEA procedural outcomes, regional variation existed in CEA and CAS outcomes. Prior stroke and congestive heart failure were associated with adverse CEA and CAS procedural outcomes whilst ischaemic heart disease, peripheral vascular disease, diabetes mellitus, chronic renal failure, age 70 years and above and non-White ethnicity were associated with increased CEA risk. Increased deprivation was associated with CEA mortality but did not affect CAS outcomes. Similar risk factors existed for long-term stroke risk following CEA and CAS.
Conclusions: Organisational and patient-level factors have been identified for optimising the carotid intervention pathway. Implementing these findings may reduce harm in high-risk patients undergoing carotid interventions, maximising their effectiveness.

Keywords: Safety
Effectiveness
Carotid Artery Stenting
Carotid Endarterectomy
Advisor: Bulbulia, R
Landray, M
Halliday, A
Enabling feature-level interpretability in non-linear latent variable models: a synthesis of statistical and machine learning techniques

Gaining insights into complex high-dimensional data is challenging and typically requires the use of dimensionality reduction methods. These methods let us identify low-dimensional structures embedded within the data that may reveal patterns of interest. In probabilistic models, such low-dimensional structures are captured via latent variables.
In biomedical applications, e.g. in computational biology, it is common to use *linear* dimensionality reduction approaches like probabilistic PCA due to their interpretability. In machine learning, however, recently there has been substantial interest in non-linear "black box" latent variable models because of their improved predictive capabilities. In this thesis, we build upon and propose extensions to two non-linear dimensionality reduction frameworks: the Gaussian Process Latent Variable Model (GPLVM) and the Variational Autoencoder (VAE). The former is based on Gaussian Processes, whereas the latter utilises neural networks. It would be desirable if we could combine some interpretable aspects of linear models with the flexibility of modern non-linear probabilistic methods.
The goal of our work is to enable feature-level interpretability within non-linear latent variable models, while also incorporating covariate information. As opposed to post-hoc explainability, we aim to directly construct decomposable non-linear models. By combining ideas from classical statistics and embedding these within latent variable models, we investigate two different perspectives on how to aid feature-level transparency. First, we propose approaches to characterise and quantify the contribution of a particular latent variable (or a covariate) for every feature. We achieve this by building upon the notion of functional ANOVA decompositions from classical statistics, and embedding these decompositions within the GPLVM and the VAE frameworks. Second, we investigate another approach towards improving feature-level interpretability, by providing a mechanism to answer the question which features exhibit similar patterns in the VAE framework. We propose to do this by introducing probabilistic clustering structure as part of the decoder network. We demonstrate the utility of our proposed methods on various toy and high-dimensional genomics data sets.

Keywords: Latent Variable Models
Non-linear dimensionality reduction
Variational Autoencoders
Interpretable Machine Learning
Bayesian Statistics
Advisor: Holmes, C
Yau, C
Revolutionary discourse and policy process: the complexities of operation production in Mozambique, 1962–1992

In 1983, the Front for the Liberation of Mozambique (Frelimo) adopted Operation Production (OP), aiming, at least in discourse, at transforming the “unproductive people” deemed to be the cause of urban chaos into “productive people”, largely through agriculture in rural Mozambique. At its end in 1988, between 40,000 to 100, 000 people had been sent to rural Mozambique. Based on the analysis of the Frelimo leadership’s ideology and values, triangulated with oral stories of those subject to OP, information from the local and international press, in-depth interviews with members of the Frelimo leadership, mid-low-level state officials, Mozambican National Resistance (Renamo) members, workers from state companies, and observation from the field, this thesis tells the story of the making, implementation and end of OP through a retrospective analysis. It starts with a discussion of the colonial-period ideological construction that led to its urban management model. Then, it explores the trajectory of the Frelimo leadership, the origin of their ideas before tackling the ways in which this past shaped Frelimo’s imaginary of urban order that led to OP. The thesis then explores the relationship between ideology, imaginary and policy choice, and its implementation. Finally, it addresses the ways in which OP ended. I argue that the Frelimo leadership’s ideas, values and imaginary, shaped by their experience of colonial order, by their military experience during the liberation struggle, and by the socio-economic and political context of the 1970s and the 1980s, was decisive in the making and implementation of OP. It resulted from the Frelimo leadership’s ideology and imaginary, framed in their discourse, associated with the context of economic crisis and war of the late 1970s and the 1980s. More than increased production, emphasized in discourse, the main goal of OP was to achieve Frelimo’s urban order (the “socialist city”), which was inspired by the historical trajectory of its leadership. The way OP ended, against the Frelimo leadership’s wishes, reveals the limitation of ideology and values to maintain policy. The thesis demonstrates the importance of understanding the social and historical origins of the Frelimo leadership, their experiences and history, their ideological predisposition, and the context in which they constructed and used discourse to disentangle African politics, particularly in a highly centralized and ambitious party-state with no strong bourgeoisie or independent state bureaucracy, such as “socialist” Mozambique. The Frelimo leadership had their own perception of urban development, which can be explained through a retrospective and contextualized analysis of their discourse.

Keywords: Mozambique
Policy Process
Operation Production
Development
Advisor: Alexander, J
Deep learning for time series prediction and decision making over time

In this thesis, we develop a collection of state-of-the-art deep learning models for time series forecasting. Primarily focusing on a closer alignment with traditional methods in time series modelling, we adopt three main directions of research -- 1) novel architectures, 2) hybrid models, and 3) feature extraction. Firstly, we propose two new architectures for general one-step-ahead and multi-horizon forecasting. With the Recurrent Neural Filter (RNF), we take a closer look at the relationship between recurrent neural networks and Bayesian filtering, so as to improve representation learning for one-step-ahead forecasts. For multi-horizon forecasting, we propose the Temporal Fusion Transformer (TFT) -- an attention-based model designed to accommodate the full range of inputs present in common problem scenarios. Secondly, we investigate the use of hybrid models to enhance traditional quantitative models with deep learning components -- using domain-specific knowledge can be used to guide neural network training. Through applications in finance (Deep Momentum Networks) and medicine (Disease-Atlas), we demonstrate that hybrid models can effectively improve forecasting performance over pure methods in either category. Finally, we explore the feature learning capabilities of deep neural networks to devise features for general forecasting models. Considering an application in systemic risk management, we devise the Autoencoder Reconstruction Ratio (ARR) -- an indicator to measure the degree of co-movement between asset returns. When fed as an input into a variety of models, we show that the ARR can help to improve short-term predictions of various risk metrics.
On top of improvements in forecasting performance, we also investigate extensions to enable decision support using deep neural networks, by helping users to better understand their data. With Recurrent Marginal Structural Networks (RMSNs), we introduce a general framework to train deep neural networks to learn causal effects over time, using ideas from marginal structural modelling in epidemiology. In addition, we also propose three practical interpretability use-cases for the TFT, demonstrating how attention weights can be analysed to provide insights into temporal dynamics.

Keywords: bayesian filtering
deep neural networks
time series forecasting
Advisor: Roberts, S
Zohren, S
Four essays on applied and methodological issues in the study of subjective life satisfaction

This thesis is comprised of four empirical papers. Paper 1, entitled “People do not adapt. New analyses of the dynamic effects of own and reference income”, uses yearly GSOEP and UKHLS data to show that there is no significant adaptation to the effects of own and reference income on life satisfaction. The paper gives an in-depth explanation of why almost all previous studies found adaptation to income and explores the implications of this finding for the estimation of equivalence scales. Paper 2 (with Nhat An Trinh), entitled “Positional, mobility and reference effects: How does social class affect life satisfaction in Europe?”, assesses the effects of social class on life satisfaction. Using ESS data, the paper gives an account of the separate effects of class position, intergenerational class mobility, and reference effects of social class on life satisfaction. The paper also gives an extended discussion of the assumptions underlying Sobel’s (1981) influential ‘diagonal reference model’, which is often used in seeking to separate the effects of class destination and origin from those of class mobility. Paper 3 (with Maarten Vendrik), entitled “How threatening are transformations of happiness scales to subjective wellbeing research?”, investigates the possibility and plausibility of reversing the signs of estimated effects of explanatory variables on happiness and life satisfaction by means of positive monotonic transformations of the response scale. The paper responds to previous papers that purport to show that such reversals are possible and plausible, which would undermine the validity of most subjective wellbeing research. Fortunately for this literature, we show that such reversals are in most cases either impossible or highly implausible. Paper 4, entitled “Memories as anchors: Theoretical reflections and empirical analyses on the intrapersonal comparability of wellbeing reports”, explores the consequences of explanatory variables affecting how respondents report their wellbeing. The paper first shows that such scale-shift effects are to be expected and subsequently analyses the biases that result from them. The paper then proposes a method based on recollections of past wellbeing to correct for intrapersonal scale shifts. The proposed method is then applied to BHPS data, showing that unemployment and bereavement are likely to be associated with strong scale-shift effects.

Keywords: ordinal choice
interpersonal welfare comparisons
adaptation
differential item functionting
social class
social comparison
life satisfaction
diagonal reference model
social mobility
vignettes
reference effects
subjective wellbeing
Advisor: Vendrik, M
Nolan, B
By popular demand: voter decision making under risk

What is the role of risk in voters’ political behaviour? By Popular Demand provides a bottom up framework exploring voter decision making under risk. The manuscript explores across three distinct settings how citizens’ exposure or tolerance to risk impact their utility and how their demands translate into support for welfare spending, vote choice or the status-quo. Together, the three papers make several important theoretical and empirical contributions. The papers introduce novel measures of risk and clarify best measurement practices to avoid ecological fallacies, they emphasize the importance of private insurance, and show that risk aversion is time variant, and decreases in wealth. The manuscript concludes that risk is central to understanding changes in support for redistribution, the Left, and the status quo. Relying on research designs that account for time-invariant unobserved individual level heterogeneity, quasi-random assignment of treatment, or directly randomize the treatment, the theoretical framework is substantiated with causal evidence.

Keywords: risk
insurance
quantitative methods
causal inference
voting
Advisor: Rueda, D
King, D