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The international laws of civil and colonial wars: A history, 1918-1949
Get PDFThis thesis interrogates, from the perspective of legal history, the particular legal constructs that international law has developed to capture civil and colonial wars as objects of international legal (ir)relevance. At the same time, it is a story of the distribution – or lack thereof – of rights, duties, status and privileges to various political communities and actors involved in the affair of civil and colonial wars. The angle proposed is a legal history of the international legal discourses produced during the period between 1918 and 1949. Including both the interwar period and the Second World War and its aftermath, this period differs from more traditional periodisations. But when tailor-made for the specific question of the relationship between international law and civil and colonial wars, the work of periodisation reveals 1918-1949 as a decisive yet under-researched period of legal history. One of the claims made in this thesis is that civil and colonial wars followed distinct trajectories within the legal discourses produced between 1918 and 1949. Their integration within a shared legal category with the 1949 Geneva Conventions constitutes, in this sense, something of a historical anomaly.
This thesis examines the reproduction of legal discourses inherited from the late nineteenth century, their transformation, as well as the challenges they faced from emerging, experimental, and sometimes short-lived legal discourses. The core argument is that 1918-1949 is a crucial period whereby traditional legal discourses on civil and colonial wars either lost their grip or reach their limits to the point that they became increasingly impractical and vulnerable to discursive rivals. They were discourses, although still dominant, whose structures became unsuitable terrains for translating the many projects pursued by various actors belonging to the discipline of international law or using its language.
In the case of civil wars, the traditional discourses of state-centrism came to be either rejected or radically re-imagined, whereas the discourse of humanitarianism experienced a substantial transformation allowing it to extend its reach to civil wars. A more institutional vision led to the emergence of legal discourses in which civil war was seen as a crucial aspect of the international legal order, directing it towards localising and suppressing civil wars. Conversely, in the case of colonial wars, the traditional discourse of ‘civilisation’ proved its robustness. But it did so in revealing its own inability to fulfil beyond a cosmetic way the logic of ‘conditional inclusion’ upon which it was nevertheless founded. Colonial war remained the limit situation of the period in which the strongest exclusive dimensions of the discourse of civilisation not only endured but were also pushed to their paroxysmal logics
Development of a home based resistance exercise programme for muscle strength and function during weight loss
Get PDFBackground:
The prevalence of obesity continues to increase, representing a major public health concern across the globe. While dietary interventions can reduce body mass, the concurrent loss of fat free mass and muscle strength is a potentially deleterious consequence. Resistance exercise may help preserve muscle mass and function during weight loss, yet its implementation remains challenging. This thesis investigated the potential of home-based resistance exercise to attenuate these deleterious effects of weight loss through three research studies.
Methods:
Study 1 included a systematic review and meta-analysis examining the effects of resistance exercise on body composition, muscle strength, and cardiometabolic health during dietary weight loss. Study 2 employed qualitative methods to explore experiences and perceptions of resistance exercise among people living with overweight or obesity (n=11), informing a theory of change for intervention development. Study 3 evaluated the effects of a 12-week home-based resistance exercise intervention, during dietary weight loss, through a randomised controlled pilot trial (n=48).
Results:
The systematic review and meta-analysis (25 RCTs) demonstrated that supervised resistance exercise during dietary weight loss preserved fat free mass (SMD: 0.40, p<0.001), increased fat mass loss (SMD: -0.36, p<0.001), and improved muscle strength (SMD: 2.36, p<0.001) relative to a no exercise control. The qualitative study identified multiple barriers, including pandemic-related limits, access to facilities and financial constraints to traditional gym-based resistance exercise, and indicated strong preferences for home-based alternatives. The pilot trial showed that, during weight loss, home-based resistance training improved grip strength (p=0.046), knee extensor maximal voluntary contraction force (p=0.019) and sit-to-stand performance (p<0.001), but did not have any effects on body composition (body mass index, total body mass, fat mass, fat free mass, muscle thickness) compared to dietary weight loss alone.
Conclusions:
The current thesis demonstrates that supervised resistance exercise enhances the benefits of diet induced weight loss by preserving muscle mass and improving muscle function. The development and evaluation of a home-based programme showed promising results for overcoming traditional barriers to resistance exercise participation and improving muscle strength and function, but not muscle mass. These findings support the implementation of accessible resistance exercise interventions during weight loss for people living with overweight or obesity
Clara Schumann, concert programming and the formation of canons: An examination of the relationship between Clara Schumann’s concert programming and the formation of musical canons in Leipzig, Vienna and London
Get PDFThis thesis examines the public performing career of Clara Schumann in Leipzig, Vienna and London through her concert programmes and the critical response to her performances. The development of her programmes and the understanding of them by critics is used to inform our understanding of Clara Schumann’s particular influence on the development of musical canons in these three cities, and to examine the way in which canons developed differently in these locations. This thesis has been helped enormously by the generosity of Reinhard Kopiez, Andreas Lehmann and Janina Klassen, in allowing me access to their database of Clara Schumann’s playbills created for their 2009 article ‘Clara Schumann's collections of playbills: a historiometric analysis of life-span development, mobility, and repertoire canonization’
Perceptual flexibility in native and non-native speech perception and sentence processing: listener’s attention shifting across speech units and attention weight on cues
Get PDFTwo overarching questions within the realm of speech perception and comprehension have been asked: Why is perceiving native speech effortless, while processing non-native speech is challenging? In this thesis, I address these questions by exploring how native and non-native listeners differ in their perceptual flexibility. I apply the concept of perceptual flexibility as a cognitive mechanism of listeners to shed light on the potential differences demonstrated by native and non-native listeners. This mechanism refers to how listeners adapt to variations in acoustic signals during speech perception and comprehension. Listeners with high perceptual flexibility are predicted to actively shift attention across and detect speech units of different sizes during real-time speech unit perception, and to assign attention weights to and flexibly integrate multiple cues during real-time sentence processing. In contrast, listeners with reduced perceptual flexibility are predicted to be less able to actively shift attention across units of different sizes and to rely consistently on certain cues with a reduced ability to integrate multiple cues. Therefore, I pose a general question: Do non-native listeners exhibit comparable perceptual flexibility to native listeners in speech unit perception and sentence processing? This thesis employs monitoring and visual-world eye-tracking paradigms to test listeners’ perceptual flexibility, which is manifested in both low-level speech perception detecting perceptual units of different sizes—and high-level sentence processing—utilizing and integrating multiple cues.
Experiments 1 and 2 are phoneme and syllable monitoring experiments using English (Experiment 1) and Mandarin (Experiment 2) pseudo-words. In each experiment there was a native listener group (English native speakers in Experiment 1, Mandarin native speakers in Experiment 2) and a non-native group (Mandarin native speakers learning English as L2 in Experiment 1, English native speakers learning Mandarin as L2 in Experiment 2). To observe how listeners flexibly shift their attention between phonemes and syllables, I manipulated the stimuli in two ways. First, I created stimuli with an artificial accent, which served as bottom-up information. Second, I used prior knowledge of the artificial accent as top-down information. I then examined how reaction times (RTs) to phoneme and syllable targets changed under these manipulations. The results revealed that both English and Mandarin listeners exhibited comparable perceptual flexibility in detecting units of different sizes in the English context (Experiment 1), with greater sensitivity to syllables than to phonemes. In the Mandarin context (Experiment 2), English listeners showed higher perceptual flexibility than Mandarin listeners. These findings shed light on how perceptual units are represented and retrieved during native and non-native speech unit perception, providing experimental support that syllable processing is more easily disrupted than phoneme processing, especially by distorted bottom-up input, suggesting that phonemes may be a more robust unit than syllables during speech perception.
While Experiments 1 and 2 examined perceptual flexibility in perceiving sublexical units, Experiments 3 and 4 looked at sentence-level processing. Experiments 3 and 4 employed a visual-world eye-tracking paradigm with English (Experiment 3) and Mandarin (Experiment 4) sentence stimuli, and utilized native and non-native listener groups as for Experiments 1 and 2. Experiments 3 and 4 investigated how native and non-native listeners adopt different perceptual strategies during real-time sentence processing, focusing on how they allocate attention to various cues and integrate them flexibly. This eye-tracking experiment particularly focused on prosodic cues, verb semantics, and whether information is repeated or new in a broader discourse context. Results showed a complex three-way interaction among L1, prosody, and verb semantics. With both English and Mandarin stimuli, when processing sentences containing old information, non-native listeners tended to adopt perceptual strategies similar to those of native listeners. Specifically, both native and non-native listeners in both languages exhibited effect of both semantics and prosody, with the semantic effect being exaggerated when the target carried a prosodic accent. However, when processing sentences containing new information, non-native and native listeners exhibited divergent patterns, the specifics of which depended on whether the stimulus language was English or Mandarin. Native listeners can interactively combine both semantic and prosodic information across a variety of contexts. Non-native listeners can also do this, but only with familiar repeated information. In contexts when they must handle new information, their ability to integrate different cues is reduced.
Thus, the main findings of the thesis are threefold. First, in the perception of low-level sublexical speech units, native and non-native listeners generally demonstrated comparable levels of perceptual flexibility when shifting their focus flexibly and actively between phonemes and syllables, with syllable processing being more susceptible to disruption than phoneme processing. Second, in high-level sentence processing, native and non-native listeners began to show a divergence in their ability to utilize and integrate multiple cues, particularly when processing sentences containing new information. Third, during high-level sentence processing, perceptual flexibility was influenced not only by a listener’s linguistic experience but also by the characteristics of the language they were processing
Multimodal machine learning framework for outcome prediction in congenital heart disease
Get PDFCongenital Heart Disease (CHD) affects approximately 1.2 million newborns annually world wide, with around 4,600 cases occurring in the UK each year. CHD encompasses a complex set of structural heart defects that pose challenges in early diagnosis, risk stratification, and treatment planning. Traditional methods employed for predicting clinical outcomes constrained by the pronounced anatomical and functional heterogeneity, limited number of datasets, and single-modal clinical markers, which often hinders the development of generalisable models in congenital heart diseases. Recent advancements in the field of Machine Learning (ML) and Deep Learning (DL) offer opportunities to integrate multi-modal data sources, thereby enabling a more comprehensive understanding of patient health. This thesis explores a multi-modal machine learning framework designed to improve CHD classification and outcome prediction, by integrating multi-modal data and geometric learning.
A significant challenge encountered during the course of this research is the heterogeneity characteristic of clinical data sources. Patient records contain Electrocardiogram (ECG) signals, cardiopulmonary exercise testing metrics and unstructured clinical documentation, each with different formats and level of completeness. Furthermore, the inherent anatomical and physiological heterogeneity of CHD increases the complexity of predictive performance. It is important to note that a model trained on one subtype may exhibit suboptimal performance when applied to a different CHD presentation, making generalisation across diverse patient populations a challenge. This thesis attempts to bridge these gaps by leveraging Riemannian geometry for the purpose of feature extraction, employing covariance augmentations to generate more data, and utilising multi-modal data integration to maximise predictive potential.
Risk prediction models are statistical or machine learning-based frameworks designed to estimate the likelihood of future adverse events for a given patient or population. In the domain of cardiology, these models facilitate predictions about a variety of outcomes, including the risk of mortality and the progression of the disease. This, in turn, serves to inform the development of early intervention and treatment strategies. They often rely on features extracted from clinical data, including ECGs, laboratory results, imaging data, and patient demographics to generate meaningful insights. However, developing accurate risk prediction models with small sample sizes presents several challenges such as limited generalisation, high variance, reduced reliability, and an insufficient representation of rare cases, particularly due to the low prevalence of related events and the inherent imbalances in datasets. Furthermore, models constructed solely on mortality data often suffer from significant imbalances, which can compromise their predictive performance. To address these challenges, this thesis explores the use of Cardiopulmonary Exercise Testing (CPET) as a surrogate for mortality, providing a novel approach to enhance model accuracy even with limited data. This key contribution not only aims to improve the reliability of risk predictions but also demonstrates the potential for developing robust predictive models that can better inform clinical decisions and improve patient outcomes in the CHD population.
Geometric deep learning can be defined as a subfield of machine learning that involves the utilisation of manifold-based, or topology-aware methodologies, for the extraction of features from structured data. Unlike conventional deep learning models, which assume inputs are organised in a regular format, such as image or text, geometric deep learning preserves spatio-temporal relationships and dependencies inherent in medical signals like ECGs. In this thesis, the covariance structure of ECG signals plays a fundamental role in enhancing risk prediction models, given that ECG readings exhibit correlated variations across different leads. The utilisation of covariance matrices to represent signals in Riemannian space ensures the preservation of higher-order relationships and can generate more stable and generalisable features, thereby reducing the impact of small sample sizes.
Machine learning applications in CHD research have traditionally focused on heartbeat classification, arrhythmia detection, and patient risk stratification based primarily on ECGs interpretation. While deep learning architectures have demonstrated promising results, challenges remain in model generalisability, dataset diversity, and clinical utility. This thesis explores the development of a multi-modal machine learning framework designed to incorporate a variety of clinical indices. The framework utilises multiple data modalities including medical health records and ECGs, with the objective of enhancing the precision and reliability of outcome prediction models. Furthermore, regression models are employed to assess cardiopulmonary exercise test results, providing insights into cardiac function of the patients. Text-mining techniques are also applied to extract meaningful clinical information from physician notes, enabling richer data-driven assessments of patient conditions.
By leveraging multiple data modalities, including medical health records and ECGs, this research aims to enhance the precision and reliability of outcome prediction models by providing a more comprehensive understanding of patient health. The scope encompasses the identification and digitisation of multiple data sources, the design and implementation of relevant machine learning models, and the evaluation of the framework’s performance in clinical settings. The integration of multi-modal data enhances the ability to capture complex cardiac abnormalities, thus offering a more comprehensive approach to diagnosis. The findings from this thesis contribute to the growing research on machine learning and congenital heart disease outcomes. We present a data-driven pathway for improving classification and outcome prediction, addressing key challenges such as imbalanced datasets, model generalisability and multi-modal data integration. By expanding dataset accessibility, future research can enhance the application of machine learning models in CHD, thus supporting clinical decision-making and improving patient care
Identifying E-type and N-type morb picrites from Paallavvik Island, Baffin Island, Canada
Get PDFA new suite of 27 igneous rocks were collected during a 2021 expedition to Paallavvik Island, funded by Red Bull. Picrites from Baffin Island have been previously investigated due to their high MgO of up to 22 wt.%, high 3He/4He ratio of 49.5Ra and the two geochemical distinct types of N-type and E-type MORB (Francis, 1985; Robillard et al., 1992; Fitton et al.; 1997; Mahoney et al., 2002; Stuart et al., 2003; Yaxley et al., 2004; Starkey, 2009; Maisonneuve, 2012). Within this study, the geochemistry and mineralogy of the new suite of igneous rocks were investigated and compared to previously published data.
Using XRF and LA-ICP-MS, the samples were analysed and then split into the two groups, N type and E-type MORB. The conditions of separation used were K/Ti 0.2 and (La/Sm)N 0.8, where less than for both conditions meant N-type MORB and more than meant E-type MORB (Robillard et al., 1992; Mahoney et al, 2002; Stuart et al., 2003; Starkey, 2009; Starkey et al., 2009; Maisonneuve, 2012). Using SEM, EMPA and LA-ICP-MS, the mineralogy and geochemistry of the minerals were investigated.
The major and trace element relationships against MgO were found to agree with previously published results (Francis, 1985; Robillard et al., 1992; Holm et al., 1993; Larsen and Pedersen, 2000; Yaxley et al., 2004; Starkey, 2009; Starkey et al., 2009). Using the conditions of separation, samples were split into 3 categories – N-type MORB, E-type MORB and those that failed one condition but not the other. N-type MORB samples were found to be 1, 4, 6, 7, 9, 13, 15, 16, 24 and 25. E-type MORB samples were 3, 5, 10, 12, 14, 20, 21, 23 and 26.
Contamination by mantle metasomatism was investigated after it was found that the Na2O/TiO2 ratio agrees with other studies at ~1.48 (σ = 0.31) for these samples, meaning that the lavas erupted through thick lithosphere and so have the potential to be contaminated (Su, 2003; Jackson and Dasgupta, 2008; Starkey, 2009). However, the investigation was inconclusive due to poor quality of data.
The olivine minerals analysed had a forsterite range of Fo34 to Fo79. In comparison to previously published studies, this is around 10% less, which may have been down to the standards used (Francis, 1985; Larsen and Pedersen, 2000; Starkey, 2009; Maisonneuve, 2012). Continuous trends of CaO, NiO and Fo% against Cr2O3, as well as no difference in Fo% for different sizes of olivines showed that the olivines are all sampling the same source (Starkey, 2009; Starkey et al., 2012).
Further work is advised for the study of the samples. By measuring 3He/4He of the melt inclusions and comparing it with previously published studies – e.g. Stuart et. al. , 2003. This will show whether the samples have a relationship with a primitive undegassed mantle reservoir. Furthermore, SIMS should also be used to investigate hydrogen and nitrogen isotopes within the melt inclusions and surrounding minerals. Hydrogen and nitrogen isotopes can help determine how the Earth became rich in volatiles and offer more information about the geochemistry of the deep mantle
An investigation into the influence of the systemic inflammatory response on treatment response to neoadjuvant chemoradiotherapy in rectal cancer
Get PDFAn abnormal systemic inflammatory response is associated with adverse short and long term outcomes in cancer. Systemic inflammation can be a surrogate maker of the interaction between host immune response and tumour. Systemic inflammation can influence treatment response to chemoradiotherapy. At present there is no reliable biomarker of response to chemoradiotherapy in rectal cancer. This thesis examines the influence of the systemic inflammatory response on treatment response to neoadjuvant chemoradiotherapy in rectal cancer.
A dataset of patients receiving neoadjuvant long course chemoradiotherapy (CRT) for non metastatic disease followed by potentially curative resection for rectal cancer was compiled from two prospectively databases of patients treated at Glasgow Royal Infirmary from 2008-2014 and the wider West of Scotland between 2014-2016. Blood results and clinic-pathological data for these patients were collected from electronic patient records to create a comprehensive dataset. Biomarkers of systemic inflammation included: differential blood count; neutrophil to lymphocyte ratio (NLR); haemoglobin; C reactive protein; albumin; and modified Glasgow Prognostic Score(mGPS). Treatment response to chemoradiotherapy was quantified with tumour regression grade, pathological complete response and the neoadjuvant rectal score.
I observed white cell count (WCC), NLR and mGPS were not associated with treatment response. Lower haemoglobin and elevated CEA were associated with poorer tumour response. There was no association with changes in WCC, NLR, CRP and tumour
response. I observed the development of lymphopenia during treatment but no association with tumour response. I observed baseline anaemia was associated with poorer tumour response and an association between anaemia and systemic inflammation. A significant proportion of my time was in the recruitment and coordination of sample collection for a novel pilot study for the feasibility of protocolised blood and tumour sampling during neoadjuvant therapy.
I have not demonstrated an association between serum markers of systemic inflammation and treatment response. I have demonstrated anaemia is a marker of poor response and the association between anaemia and systemic inflammation. This highlights the difficulty in measurements of the systemic inflammatory response from routine blood tests and the importance of more detailed study of markers of systemic inflammatory response which are being done in research settings rather than routine clinical practice. This would help identify reliable biomarkers of treatment response to neoadjuvant chemotherapy and organ preservation strategies
The role of the transcriptional regulator TANDEM ZINC-FINGER PLUS3 in regulating light and temperature signalling in Arabidopsis thaliana
No full textAbstract not currently available
A two-stage Bayesian modelling framework with applications in spatial epidemiology
Get PDFThis thesis proposes a framework for doing two-stage modelling in spatial epidemiology, whose main goal is to understand the association between a covariate of interest, which is modelled in the first stage, and health outcomes, which is modelled in the second stage using the first-stage model predictions as inputs. A two-stage modeling framework has the advantage of being more computationally efficient than a joint modelling approach when the first-stage model is already complex in itself, and avoids the potential problem of unwanted feedback effects, which happen when the second-stage data affect first-stage model inference. Chapter 1 discusses the motivation behind this research. The specific data application of this thesis links dengue incidence and climate variables, particularly temperature, relative humidity, and rainfall, in the Philippines. Dengue is an infectious disease caused by Aedes mosquitoes, and which poses significant socioeconomic and disease burden in many tropical and subtropical regions of the world.
In a two-stage modelling framework, the first stage fits the model for the main covariate of interest, whose association with the health outcome is investigated. In the data application, the first-stage fits climate models, which are then used to predict the true climate field over the entire spatial domain. The data limitation, which poses challenges on the accuracy of model inference and predictions, is the sparsity in the data from weather stations. This data problem is overcome by incorporating additional data sources (referred to as proxy data), albeit more biased but with wider spatial coverage, and then combining the different data sources in a process called data fusion, whose main goal is the improvement of model accuracy. Chapter 3 presents an initial exploration of a data fusion Bayesian model estimated using integrated nested Laplace approximation (INLA). Chapter 4 presents a flexible model specification of the data fusion model, which is shown to outperform benchmark approaches in terms of the accuracy of model predictions and parameter estimates. The proposed model specifies both a time-varying random field to account for the additive bias and a constant multiplicative bias parameter in the proxy data. Chapter 4 also presents the results from applying the proposed data fusion model on the meteorological data in the Philippines. The results of leave-group-out cross validation show that the data fusion model outperforms benchmark approaches.
Chapter 5 presents results from an extensive analysis on the link between climate and dengue occurrence in the Philippines. The predicted climate fields from Chapter 4 are used as inputs to the health model. To account for the uncertainty in the predictions from the climate models, a resampling approach is used, which generates samples from the first-stage model posteriors and where each sample is used as an input to the second-stage model. The final posterior estimates of second-stage model parameters are then computed using Bayesian model averaging. The results show that temperature has a non-linear relationship with dengue occurrence. In particular, temperature is generally positively related to dengue, but very hot conditions tend to have a negative impact. Moreover, the relationship between rainfall and dengue varies in space, depending on the climate type of the area. For areas with uniform and low variation in the amount of rainfall all year round, rainfall is negatively associated with dengue, while for areas with pronounced dry and wet season, rainfall is positively related with dengue. This is potentially explained by the fact that consistent rainfall tends to wash away mosquito breeding sites, while sporadic rainfall during dry season tends to create more breeding sites.
Chapter 6 investigates the correctness of the two approaches for doing two-stage modelling used in Chapter 5, particularly the crude plug-in approach, which simply plugs in the posterior mean of the first-stage (climate) model parameters to the second-stage (health) model, and the resampling approach. I used the simulation-based calibration (SBC) approach, which tests the self-consistency property of Bayesian models, to validate the correctness of the aforementioned approaches. Results show that the crude plug-in method indeed underestimates the posterior uncertainty in the second-stage model parameters, while the resampling approach is correct. This chapter also proposes a new approach for doing uncertainty propagation, called the Q uncertainty method, which introduces a new model component called the error component. The Q−1 matrix essentially encodes the uncertainty in the first-stage latent parameters. In addition, I proposed a low rank approximation of the Q matrix, which can be useful for large spatio-temporal applications. I also used the SBC method to validate the correctness of the proposed method. Results of model validation on toy spatial models show that the Q method can be correct, but the accuracy of the posterior approximations and the computational benefits of the method depends on the coarseness of the mesh for the error component and the dimension of the first-stage model latent parameters. The main reasons for the computational bottleneck with the proposed method is that the predictor expression of the Q method involves non-linear model components, which does not fit quite conveniently in the INLA framework.
Finally, Chapter 7, the conclusion chapter, highlights the main contributions of this thesis and outlines potential directions for future work. In addition, I reemphasize current approaches for fitting conditional latent Gaussian models, and provide ideas on a new approach for fitting such models. Whereas the previous chapters highlight the problem of spatial misalignment, the final chapter discusses the issue of time misalignment. I provide ideas and initial results from using INLA to fit Mixed-Data-Sampling (MIDAS) models, which provide a framework for fitting a regression model on time series data with varying frequencies
An autoethnographic inquiry into the sources of inspiration for a feminist fantasy novel: a Druid author’s experience
No full textThis work comprises two parts, a critical element utilising an autoethnographical approach to explore intuition, and a novel The Maiden’s Tale: Ròn, which resulted directly from the practice-based research employed.
The novel, intended as the first book in a trilogy begins in the Neolithic era and is a fantasy involving Merus, an ephemeral energy who guide humanity. It speculates on the lost knowledge of women focusing on their roles as ‘midwives’ and spiritual leaders, with the balance of feminine and masculine energies as the principal thread.
The story of The Maiden’s Tale: Ròn was pursued through a Quest, an aspect of spiritual practice as a Druid, working with Tarot cards in meditation as a portal to another reality. The critical writing centres experiences in the collected field work of diary entries, journalling, memoir and life writing, interspersed with discussions of the themes encountered, primarily through the concept of synchronicity. Aspects of reality are considered regarding identities as a writer, a Druid, and a midwife. Being spiritually led, subjectivity and belief drive the narrative of thought which offers a unique insight into creativity and the discovery of a distinctive technique of seeking intuition for the purposes of creative writing – Sha-awen.The research for a fictional story became entwined with the critical examination culminating in an inextricable link between the two, a symbiotic influencing
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