14,181 research outputs found
Victims' Access to Justice in Trinidad and Tobago: An exploratory study of experiences and challenges of accessing criminal justice in a post-colonial society
This thesis investigates victims' access to justice in Trinidad and Tobago, using their own narratives. It seeks to capture how their experiences affected their identities as victims and citizens, alongside their perceptions of legitimacy regarding the criminal justice system. While there have been some reforms in the administration of criminal justice in Trinidad and Tobago, such reforms have not focused on victims' accessibility to the justice system. Using grounded theory methodology, qualitative data was collected through 31 in-depth interviews with victims and victim advocates. The analysis found that victims experienced interpersonal, structural, and systemic barriers at varying levels throughout the criminal justice system, which manifested as institutionalized secondary victimization, silencing and inequality. This thesis argues that such experiences not only served to appropriate conflict but demonstrates that access is often given in a very narrow sense. Furthermore, it shows a failure to encompass access to justice as appropriated conflicts are left to stagnate in the system as there is often very little resolution. Adopting a postcolonial lens to analyse victims' experiences, the analysis identified othering practices that served to institutionalize the vulnerability and powerlessness associated with victim identities. Here, it is argued that these othering practices also affected the rights consciousness of victims, delegitimating their identities as citizens. Moreover, as a result of their experiences, victims had mixed perceptions of the justice system. It is argued that while the system is a legitimate authority victims' endorsement of the system is questionable, therefore victims' experiences suggest that there is a reinforcement of the system's legal hegemony. The findings suggest that within the legal system of Trinidad and Tobago, legacies of colonialism shape the postcolonial present as the psychology and inequalities of the past are present in the interactions and processes of justice. These findings are relevant for policymakers in Trinidad and Tobago and other regions. From this study it is recognized that, to improve access to justice for victims, there needs to be a move towards victim empowerment that promotes resilience and enhances social capital. Going forward it is noted that there is a need for further research
Embodying entrepreneurship: everyday practices, processes and routines in a technology incubator
The growing interest in the processes and practices of entrepreneurship has
been dominated by a consideration of temporality. Through a thirty-six-month
ethnography of a technology incubator, this thesis contributes to extant
understanding by exploring the effect of space. The first paper explores how
class structures from the surrounding city have appropriated entrepreneurship
within the incubator. The second paper adopts a more explicitly spatial analysis
to reveal how the use of space influences a common understanding of
entrepreneurship. The final paper looks more closely at the entrepreneurs within
the incubator and how they use visual symbols to develop their identity. Taken
together, the three papers reject the notion of entrepreneurship as a primarily
economic endeavour as articulated through commonly understood language and
propose entrepreneuring as an enigmatic attractor that is accessed through the
ambiguity of the non-verbal to develop the ‘new’. The thesis therefore contributes
to the understanding of entrepreneurship and proposes a distinct role for the non-verbal in that understanding
Women’s Experiences of Accessing Breastfeeding and Perinatal Health Support in the Context of Intimate Partner Violence: An Interpretive Description Study
Background: Women experiencing intimate partner violence are at a heightened risk of negative perinatal and breastfeeding outcomes. This study explored the experiences of accessing breastfeeding support for women who endorse a history of intimate partner violence. A study of five in-depth semi-structured interviews were completed at 12-weeks postpartum with breastfeeding mothers with a history of intimate partner violence. Findings: Women expressed difficulties in accessing a healthcare provider who had specialized skill in breastfeeding support. Trust in their healthcare provider, built through displays of compassion and competence, was important to mitigate obstacles experienced during care access for this population. Trauma-and-violence-informed care principles were beneficial to the development of the therapeutic relationship in perinatal care. Women placed value on breastfeeding support received from both healthcare providers and social supports, which impacted mothers’ perceived breastfeeding support and self-efficacy. Further, mothers described increased levels of breastfeeding self-efficacy after engaging in a trauma-and-violence-informed care program aimed at supporting breastfeeding. Conclusions: Trauma-informed care may aid in the development of trust in the therapeutic relationship, which in turn impacts access to breastfeeding support and breastfeeding self-efficacy. The inclusion of trauma-and-violence informed principles in perinatal care may be effective at mitigating barriers to access for women who endorse a history of intimate partner violence. health care on how to employ trauma-informed breastfeeding care to may lead to better support for this population
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Reliable Decision-Making with Imprecise Models
The rapid growth in the deployment of autonomous systems across various sectors has generated considerable interest in how these systems can operate reliably in large, stochastic, and unstructured environments. Despite recent advances in artificial intelligence and machine learning, it is challenging to assure that autonomous systems will operate reliably in the open world. One of the causes of unreliable behavior is the impreciseness of the model used for decision-making. Due to the practical challenges in data collection and precise model specification, autonomous systems often operate based on models that do not represent all the details in the environment. Even if the system has access to a comprehensive decision-making model that accounts for all the details in the environment and all possible scenarios the agent may encounter, it may be intractable to solve this complex model optimally. Consequently, this complex, high fidelity model may be simplified to accelerate planning, introducing imprecision. Reasoning with such imprecise models affects the reliability of autonomous systems. A system\u27s actions may sometimes produce unexpected, undesirable consequences, which are often identified after deployment. How can we design autonomous systems that can operate reliably in the presence of uncertainty and model imprecision?
This dissertation presents solutions to address three classes of model imprecision in a Markov decision process, along with an analysis of the conditions under which bounded-performance can be guaranteed. First, an adaptive outcome selection approach is introduced to devise risk-aware reduced models of the environment that efficiently balance the trade-off between model simplicity and fidelity, to accelerate planning in resource-constrained settings. Second, a framework that extends stochastic shortest path framework to problems with imperfect information about the goal state during planning is introduced, along with two solution approaches to solve this problem. Finally, two complementary solution approaches are presented to minimize the negative side effects of agent actions. The techniques presented in this dissertation enable an autonomous system to detect and mitigate undesirable behavior, without redesigning the model entirely
The Role of English and Welsh INGOs: A Field Theory-Based Exploration of the Sector
This thesis takes a field theory-based approach to exploring the role of English and Welsh international non-governmental organisations (INGOs), using the lens of income source form.
First, the thesis presents new income source data drawn from 933 Annual Accounts published by 316 INGOs over three years (2015-2018). The research then draws on qualitative data from 90 Leaders' letters include within the Annual Reports published by 39 INGOS, as well as supplementary quantitative and qualitative data, to explore the ways in which INGOs represent their role.
Analysis of this income source data demonstrates that government funding is less important to most INGOs than has previously been assumed, while income from individuals is more important than has been recognised in the extant development studies literature. Funding from other organisations within the voluntary sector is the third most important source of income for these INGOs, while income from fees and trading is substantially less important than the other income source forms.
Using this income source data in concert with other quantitative data on INGO characteristics as well as qualitative data drawn from the Leaders' letters, I then show that the English and Welsh INGO sector is a heterogenous space, divided into multiple fields. The set of fields identified by this thesis is arranged primarily around income source form, which is also associated with size, religious affiliation, and activities of focus and ways of working. As Bourdieusian field theory suggests, within these fields individual INGOs are engaged in an ongoing struggle for position: competing to demonstrate their maximal possession of the symbolic capitals they perceive to be valued by (potential) donors to that field.
Further analysis of these Leaders' letters, alongside additional Annual Reports and Accounts data, also reveals a dissonance in the way in which INGOs describe their relationship with local partners in these different communication types. While these Leaders' letters and narrative reports tell stories of collaborative associations with locally-based partners, this obscures the nature of these relationships as competitive and hierarchical.
The thesis draws on the above findings to reflect on the role of INGOs as suggested in the extant literature. This discussion highlights how the various potential INGO fields identified are associated with differing theoretical roles for INGOs. Finally, the thesis considers how INGO role representations continue to contribute to unequal power relations between INGOs and their partners
Response of saline reservoir to different phaseCOâ‚‚-brine: experimental tests and image-based modelling
Geological CO₂ storage in saline rocks is a promising method for meeting the target of net zero emission and minimizing the anthropogenic CO₂ emitted into the earth’s atmosphere. Storage of CO₂ in saline rocks triggers CO₂-brine-rock interaction that alters the properties of the rock. Properties of rocks are very crucial for the integrity and efficiency of the storage process. Changes in properties of the reservoir rocks due to CO₂-brine-rock interaction must be well predicted, as some changes can reduce the storage integrity of the reservoir. Considering the thermodynamics, phase behavior, solubility of CO₂ in brine, and the variable pressure-temperature conditions of the reservoir, there will be undissolved CO₂ in a CO₂ storage reservoir alongside the brine for a long time, and there is a potential for phase evolution of the undissolved CO₂. The phase of CO₂ influence the CO₂-brine-rock interaction, different phaseCO₂-brine have a unique effect on the properties of the reservoir rocks, Therefore, this study evaluates the effect of four different phaseCO₂-brine reservoir states on the properties of reservoir rocks using experimental and image-based approach.
Samples were saturated with the different phaseCOâ‚‚-brine, then subjected to reservoir conditions in a triaxial compression test. The representative element volume (REV)/representative element area (REA) for the rock samples was determined from processed digital images, and rock properties were evaluated using digital rock physics and rock image analysis techniques. This research has evaluated the effect of different phaseCOâ‚‚-brine on deformation rate and deformation behavior, bulk modulus, compressibility, strength, and stiffness as well as porosity and permeability of sample reservoir rocks. Changes in pore geometry properties, porosity, and permeability of the rocks in COâ‚‚ storage conditions with different phaseCOâ‚‚-brine have been evaluated using digital rock physics techniques. Microscopic rock image analysis has been applied to provide evidence of changes in micro-fabric, the topology of minerals, and elemental composition of minerals in saline rocks resulting from different phaseCOâ‚‚-br that can exist in a saline COâ‚‚ storage reservoir. It was seen that the properties of the reservoir that are most affected by the scCOâ‚‚-br state of the reservoir include secondary fatigue rate, bulk modulus, shear strength, change in the topology of minerals after saturation as well as change in shape and flatness of pore surfaces. The properties of the reservoir that is most affected by the gCOâ‚‚-br state of the reservoir include primary fatigue rate, change in permeability due to stress, change in porosity due to stress, and change topology of minerals due to stress. For all samples, the roundness and smoothness of grains as well as smoothness of pores increased after compression while the roundness of pores decreased. Change in elemental composition in rock minerals in COâ‚‚-brine-rock interaction was seen to depend on the reactivity of the mineral with COâ‚‚ and/or brine and the presence of brine accelerates such change. Carbon, oxygen, and silicon can be used as index minerals for elemental changes in a COâ‚‚-brine-rock system. The result of this work can be applied to predicting the effect the different possible phases of COâ‚‚ will have on the deformation, geomechanics indices, and storage integrity of giant COâ‚‚ storage fields such as Sleipner, In Salah, etc
In search of 'The people of La Manche': A comparative study of funerary practices in the Transmanche region during the late Neolithic and Early Bronze Age (250BC-1500BC)
This research project sets out to discover whether archaeological evidence dating between 2500 BC - 1500 BC from supposed funerary contexts in Kent, flanders and north-eastern Transmanche France is sufficient to make valid comparisons between social and cultural structures on either side of the short-sea Channel region. Evidence from the beginning of the period primarily comes in the form of the widespread Beaker phenomenon. Chapter 5 shows that this class of data is abundant in Kent but quite sparse in the Continental zones - most probably because it has not survived well. This problem also affects the human depositional evidence catalogued in Chapter 6, particularly in Fanders but also in north-eastern Transmanche France. This constricts comparative analysis, however, the abundant data from Kent means that general trends are still discernible. The quality and volume of data relating to the distribution, location, morphology and use of circular monuments in all three zones is far better - as demonstrated in Chapter 7 -mostly due to extensive aerial surveying over several decades. When the datasets are taken as a whole, it becomes possible to successfully apply various forms of comparative analyses. Most remarkably, this has revealed that some monuments apparently have encoded within them a sophisticated and potentially symbolically charged geometric shape. This, along with other less contentious evidence, demonstrates a level of conformity that strongly suggests a stratum of cultural homogeneity existed throughout the Transmanche region during the period 2500 BC - 1500 BC. The fact that such changes as are apparent seem to have developed simultaneously in each of the zones adds additional weight to the theory that contact throughout the Transmanche region was endemic. Even so, it may not have been continuous; there may actually have been times of relative isolation - the data is simply too course to eliminate such a possibility
Scalable software and models for large-scale extracellular recordings
The brain represents information about the world through the electrical activity of
populations of neurons. By placing an electrode near a neuron that is firing (spiking), it
is possible to detect the resulting extracellular action potential (EAP) that is transmitted
down an axon to other neurons. In this way, it is possible to monitor the communication
of a group of neurons to uncover how they encode and transmit information. As the
number of recorded neurons continues to increase, however, so do the data processing
and analysis challenges. It is crucial that scalable software and analysis tools are developed
and made available to the neuroscience community to keep up with the large
amounts of data that are already being gathered.
This thesis is composed of three pieces of work which I develop in order to better
process and analyze large-scale extracellular recordings. My work spans all stages of extracellular
analysis from the processing of raw electrical recordings to the development
of statistical models to reveal underlying structure in neural population activity.
In the first work, I focus on developing software to improve the comparison and adoption
of different computational approaches for spike sorting. When analyzing neural
recordings, most researchers are interested in the spiking activity of individual neurons,
which must be extracted from the raw electrical traces through a process called
spike sorting. Much development has been directed towards improving the performance
and automation of spike sorting. This continuous development, while essential,
has contributed to an over-saturation of new, incompatible tools that hinders rigorous
benchmarking and complicates reproducible analysis. To address these limitations, I
develop SpikeInterface, an open-source, Python framework designed to unify preexisting
spike sorting technologies into a single toolkit and to facilitate straightforward
benchmarking of different approaches. With this framework, I demonstrate that modern,
automated spike sorters have low agreement when analyzing the same dataset, i.e.
they find different numbers of neurons with different activity profiles; This result holds
true for a variety of simulated and real datasets. Also, I demonstrate that utilizing a
consensus-based approach to spike sorting, where the outputs of multiple spike sorters
are combined, can dramatically reduce the number of falsely detected neurons.
In the second work, I focus on developing an unsupervised machine learning approach
for determining the source location of individually detected spikes that are
recorded by high-density, microelectrode arrays. By localizing the source of individual
spikes, my method is able to determine the approximate position of the recorded neuriii
ons in relation to the microelectrode array. To allow my model to work with large-scale
datasets, I utilize deep neural networks, a family of machine learning algorithms that
can be trained to approximate complicated functions in a scalable fashion. I evaluate
my method on both simulated and real extracellular datasets, demonstrating that it is
more accurate than other commonly used methods. Also, I show that location estimates
for individual spikes can be utilized to improve the efficiency and accuracy of spike
sorting. After training, my method allows for localization of one million spikes in approximately
37 seconds on a TITAN X GPU, enabling real-time analysis of massive
extracellular datasets.
In my third and final presented work, I focus on developing an unsupervised machine
learning model that can uncover patterns of activity from neural populations
associated with a behaviour being performed. Specifically, I introduce Targeted Neural
Dynamical Modelling (TNDM), a statistical model that jointly models the neural activity
and any external behavioural variables. TNDM decomposes neural dynamics (i.e.
temporal activity patterns) into behaviourally relevant and behaviourally irrelevant dynamics;
the behaviourally relevant dynamics constitute all activity patterns required
to generate the behaviour of interest while behaviourally irrelevant dynamics may be
completely unrelated (e.g. other behavioural or brain states), or even related to behaviour
execution (e.g. dynamics that are associated with behaviour generally but are not
task specific). Again, I implement TNDM using a deep neural network to improve its
scalability and expressivity. On synthetic data and on real recordings from the premotor
(PMd) and primary motor cortex (M1) of a monkey performing a center-out reaching
task, I show that TNDM is able to extract low-dimensional neural dynamics that are
highly predictive of behaviour without sacrificing its fit to the neural data
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