This paper argues that Gertler’s (2012) account of acquaintance is inadequate because it cannot perform the explanatory role that it’s supposed to perform. My argument builds from two central claims. First, I argue that our judgments about phenomenal absences have the special features that acquaintance is supposed to explain. Second, I argue that Gertler’s take on acquaintance does not allow us to be acquainted with phenomenal absences. This suggests a general methodological lesson: when developing an account of the epistemology of acquaintance, we should make sure that we are capturing all of the relevant sorts of cases. / Master of Arts

Denna uppsats är en litteraturstudie av Roots: The Saga of an American Family. Studien syftar till att undersöka argumentet att rasism har en långvarig effekt på de människor som utsätts för rasism. I detta fall, karaktärerna i romanen som utsätts för rasismens olika hemskheter så som slaveri. Genom användningen av Robert Jensen, WEB Du Bois och Edward Saids teorier (dvs. Privileged/unprivileged, The Veil, Double Consciousness och Others) har romanen Roots analyserats. Slutsatsen visar på hur slaveriet påverkade huvudpersonerna och hur effekten av slaveri lyckats beröva de svarta människorna i romanen deras ursprungliga identitet. Slaveriet ersattes istället av en kollektiv identitet av mindre värde än vita människors identitet vilket lämnat långvariga psykiska ärr för karaktärerna i romanen. Det pedagogiska fokus som används i uppsatsen är den så kallad cooperative learning metoden.

Métodos de agrupamento hierárquico de textos são muito úteis para analisar o conhecimento embutido em coleções textuais, organizando os documentos textuais em grupos e subgrupos para facilitar a exploração do conhecimento em diversos níveis de granularidade. Tais métodos pertencem à área de aprendizado não supervisionado de máquina, uma que vez obtêm modelos de agrupamento apenas pela observação de regularidades existentes na coleção textual, sem supervisão humana. Os métodos tradicionais de agrupamento assumem que a coleção textual é representada apenas pela informação técnica, ou seja, palavras e frases extraídas diretamente dos textos. Por outro lado, em muitas tarefas de agrupamento existe conhecimento adicional e valioso a respeito dos dados, geralmente extraído por um processo avançado com apoio de usuários especialistas do domínio do problema. Devido ao alto custo para obtenção desses dados, esta informação adicional é definida como privilegiada e usualmente está disponível para representar apenas um subconjunto dos documentos textuais. Recentemente, um novo paradigma de aprendizado de máquina denominado LUPI (Learning Using Privileged Information) foi proposto por Vapnik para incorporar informação privilegiada em métodos aprendizado supervisionado. Neste trabalho de doutorado, o paradigma LUPI foi estendido para aprendizado não supervisionado, em especial, para agrupamento hierárquico de textos. Foram propostas e avaliadas abordagens para lidar com diferentes desafios existentes em tarefas de agrupamento, envolvendo a extração e estruturação da informação privilegiada e seu uso para refinar ou corrigir modelos de agrupamento. As abordagens propostas se mostraram eficazes em (i) consenso de agrupamentos, permitindo combinar diferentes representações e soluções de agrupamento; (ii) aprendizado de métricas, em que medidas de proximidades mais robustas foram obtidas com base na informação privilegiada; e (iii) seleção de modelos, em que a informação privilegiada é explorada para identificar relevantes estruturas de agrupamento hierárquico. Todas as abordagens apresentadas foram investigadas em um cenário de agrupamento incremental, permitindo seu uso em aplicações práticas caracterizadas pela necessidade de eficiência computacional e alta frequência de publicação de novo conhecimento textual. / Hierarchical text clustering methods are very useful to analyze the implicit knowledge in textual collections, enabling the organization of textual documents into clusters and subclusters to facilitate the knowledge browsing at various levels of granularity. Such methods are classified as unsupervised machine learning, since the clustering models are obtained only by observing regularities of textual data without human supervision. Traditional clustering methods assume that the text collection is represented only by the technical information, i.e., words and phrases extracted directly from the texts. On the other hand, in many text clustering tasks there is an additional and valuable knowledge about the problem domain, usually extracted by an advanced process with support of the domain experts. Due to the high cost of obtaining such expert knowledge, this additional information is defined as privileged and is usually available to represent only a subset of the textual documents. Recently, a new machine learning paradigm called LUPI (Learning Using Privileged Information) was proposed by Vapnik to incorporate privileged information into supervised learning methods. In this thesis, the LUPI paradigm was extended to unsupervised learning setting, in particular for hierarchical text clustering. We propose and evaluate approaches to deal with different challenges for clustering tasks, involving the extraction and structuring of privileged information and using this additional information to refine or correct clustering models. The proposed approaches were effective in (i) consensus clustering, allowing to combine different clustering solutions and textual representations; (ii) metric learning, in which more robust proximity measures are obtained from privileged information; and (iii) model selection, in which the privileged information is exploited to identify the relevant structures of hierarchical clustering. All the approaches presented in this thesis were investigated in an incremental clustering scenario, allowing its use in practical applications that require computational efficiency as well as deal with high frequency of publication of new textual knowledge.

Currently governments and research communities are concentrating on insider threat matters more than ever, the main reason for this is that the effect of a malicious insider threat is greater than before. Moreover, leaks and the selling of the mass data have become easier, with the use of the dark web. Malicious insiders can leak confidential data while remaining anonymous. Our approach describes the information gained by looking into insider security threats from the multiple perspective concepts that is based on an integrated three-dimensional approach. The three dimensions are human issue, technology factor, and organisation aspect that forms one risk prediction solution. In the first part of this thesis, we give an overview of the various basic characteristics of insider cyber-security threats. We also consider current approaches and controls of mitigating the level of such threats by broadly classifying them in two categories: a) technical mitigation approaches, and b) non-technical mitigation approaches. We review case studies of insider crimes to understand how authorised users could harm their organisations by dividing these cases into seven groups based on insider threat categories as follows: a) insider IT sabotage, b) insider IT fraud, c) insider theft of intellectual property, d) insider social engineering, e) unintentional insider threat incident, f) insider in cloud computing, and g) insider national security. In the second part of this thesis, we present a novel approach to predict malicious insider threats before the breach takes place. A prediction model was first developed based on the outcomes of the research literature which highlighted main prediction factors with the insider indicator variables. Then Bayesian network statistical methods were used to implement and test the proposed model by using dummy data. A survey was conducted to collect real data from a single organisation. Then a risk level and prediction for each authorised user within the organisation were analysed and measured. Dynamic Bayesian network model was also proposed in this thesis to predict insider threats for a period of time, based on data collected and analysed on different time scales by adding time series factors to the previous model. Results of the verification test comparing the output of 61 cases from the education sector prediction model show a good consistence. The correlation was generally around R-squared =0.87 which indicates an acceptable fit in this area of research. From the result we expected that the approach will be a useful tool for security experts. It provides organisations with an insider threat risk assessment to each authorised user and also organisations can discover their weakness area that needs attention in dealing with insider threat. Moreover, we expect the model to be useful to the researcher's community as the basis for understanding and future research.

In this thesis I examine the contemporary nexus between White women and the raced and classed institution of White womanhood. More specifically, I focus on White Australian women who are middle class, rich in cultural capital, and generally consider themselves to be progressive; that is race privileged women but women who are not usually associated with overt racism. My analysis unfolds White Australian women in the discursive context of the ideologies of feminism and feminist-influenced anti-racist politics, as well as the ideologies of femininity. The thesis shows how this nexus is enacted through a vision of White women as Good as expressed in the political commitments, mentalities, relationships, narratives and corporeality of such women. The research problem that I identified and worked through in the thesis is as follows: for middle class White women, (who can be seen and see themselves as generic 'women'), Whiteness has been seen and played out as Goodness. Further, in the playing out of this Goodness White women accumulate and defend the prestige and privileges of Whiteness. Specifically, I argue that Whiteness is reproduced in some of the discourses and practices of White feminism, by the progressive White women involved in anti-racist politics, and in the femininity industry and the ways it is taken up. The nub of the problem I identify is that White women's involvement in the structures and narratives that support Whiteness is often grounded in the very qualities of character and conduct that emerge from the colonial and class-constructed ideal of White womanhood and which have historically distinguished them from denigrated others. These qualities- notably virtue, innocence and self-restraint- whilst differently nuanced in other contexts are an ongoing expression of the uses made of White womanhood as the visible sign of race and class superiority. The work examines four key periods: the Australian colony of PNG during the decolonising 1960's and 1970's; the high years of 1970's and 1980's feminism; the race debates of the 1990's; and the bodily practices of present day White women gripped by fears of fat and aging. I explore the ways in which White women's Whiteness is played out in benevolent Black/White relationships, the over-reach of difference feminism, particular kinds of anti-racist identities and activism, and body-improvement practices. In all these cultural sites, White women's Whiteness is often represented as a kind of moral being and deployed as moral authority in ways that are consonant with the raced and classed construction of White women as moral texts. My research approach was determined by the research problem I identified. Given my argument that White women mis-recognise Whiteness as Goodness in a race-structured society, then the collecting of data through interviews or surveys would have yielded material subject to this blindness. Instead, I explored sites and material where moral claims were being pressed, and case studies where 'women' were enacting themselves or being represented or interpellated as moral texts. My selection of primary source material ranges from feminist newsletters, women's and other magazines, literature, film, event programs and flyers, radio and television broadcasts, newspapers and websites, as well as reflections on my own experiences. Secondary source material includes feminist theoretical texts as well as texts drawn from a range of other disciplines, and other historical background materials. I lay out and support my arguments using a technique not dissimilar to collage, aiming to construct a picture that is compelling in its detail as well as coherent in its overall effect. This thesis is a contribution to the de-naturalisation of Whiteness. Navigating a course between the opposing hazards of essentialising Whiteness and understating its effects in contemporary Australian society, I have brought into clearer view some of the strategies which maintain the authority of Whiteness.

Relapsing fever (RF) is a disease caused by tick- or louse-transmitted bacteria of the genus Borrelia. It occurs worldwide but is most common in Africa where it is one of the most prevalent bacterial diseases. The main manifestation is a recurring fever which coincides with massive numbers of bacteria in the blood. Severity ranges from asymptomatic to fatal. RF is usually considered a transient disease. In contrast, B. duttonii causes a persistent, residual brain infection in C57BL/6 mice which remains long time after the bacteria are cleared from the blood. The host gene expression pattern is indistinguishable from that of uninfected animals, indicating that persistent bacteria are not recognized by the immune system nor do they cause noticeable tissue damage. This is probably due to the quite low number of bacteria residing in the brain. The silent infection can be reactivated by immunosuppression allowing bacteria to re-enter the blood. To investigate if the residual infection is in a quiescent state or if the bacteria are actively dividing, mice with residual brain infection were treated with the cell-wall disrupting antibiotic ceftriaxone, which is only active against dividing bacteria. Since all mice were cured by ceftriaxone we conclude that the bacteria are actively growing in the brain rather than being in a latent, dormant state. The brain is used as an immunoprivileged site to escape host immune defence and probably as a reservoir for bacteria. RF is a common cause of pregnancy complications, miscarriage and neonatal death in sub-Saharan Africa. We established a murine model of gestational relapsing fever to study the pathological development of these complications. B. duttonii infection during pregnancy results in intrauterine growth retardation as well as placental damage and inflammation. Spirochetes cross the maternal-foetal barrier, resulting in congenital infection. Further, pregnancy has a protective effect, resulting in milder disease during pregnancy. A clinic-based study to investigate the presence of RF in Togo was performed. Blood from patients with fever were examined for RF by microscopy, GlpQ ELISA and PCR. About 10% of the patients were positive by PCR and 13% had antibodies to GlpQ. Many RF patients originally had a misdiagnosis of malaria, which resulted in ineffective treatment. The inability of microscopic analysis to detect spirochetes demonstrates the need for tests with greater sensitivity. To provide simple, fast, cheap and sensitive diagnostics using equipment available in small health centres, a method based on enrichment of bacteria by centrifugation and detection by Giemsa staining was developed which detects <10 spirochetes/ml. To study the phylogeny of RF, IGS and glpQ were sequenced and neighbor joining trees were constructed. B. persica and B. hispanica were distant from the other species iswhereas B. crocidurae appeared to be a heterogeneous species. B. duttonii is polyphyletic in relation to B. recurrentis suggesting that the two species may in fact be the same or have a polyphyletic origin.

This thesis aims to analyze German Conservatism and the impact of Germany&rsquo / s policies towards Turkey&rsquo / s membership. The point of departure is privileged partnership which is offered to Turkey in replace of membership to the EU. German Chancellor Angela Merkel is a prominent defender of privileged partnership and previous Chancellor Gerhard Schr&ouml / der who supported Turkey&rsquo / s accession, had a totally different attitude. It is questioned whether this sharp change in foreign policy derives from German Conservatism and Christian Democracy. As a result, it is not possible to claim an essentialist opposition to Turkey&rsquo / s accession by German Christian Democrats but privileged partnership is a product of German Conservative thinking which sees European Integration as a cultural project.

In Canada, progress towards reconciliation with Aboriginal Peoples has been slow, in part because of a lack of emphasis on interpersonal reconciliation—changes in the beliefs, attitudes, and behaviours of non-Aboriginal Canadians. Physical distance, prejudicial public discourses, and insufficient, ineffective education for the public pose barriers to renewed relationships between settlers and Aboriginal Peoples. Drawing from transformative learning theory and pedagogy for the privileged, this narrative inquiry examines critical events in the lives of eight white settlers living in Mi’kmaw territory in Nova Scotia. The study uncovers factors which have prompted some Euro-Canadians to take up their responsibility for reconciliation and enabled them to stand as allies with the Mi’kmaq. The transformation process in settler allies was catalyzed by a combination of personal, intrinsic, and extrinsic events. New relationships between settlers and the Mi’kmaq were founded around shared interests or goals, and friendships provided an important foundation for learning. Hearing the personal stories of Mi’kmaw people challenged stereotypes and misinformation about Aboriginal Peoples. Settlers’ learning was further supported by immersion in Mi’kmaw communities or contexts, time spent on the land, and mentoring by Mi’kmaw people. Allies reported that the satisfaction they derived from relationships with Mi’kmaw people as well as a desire to do good and see justice done sustained these relationships over the longer term. The study suggests that a lengthy period of awareness raising and confidence building followed by opportunities for informal, experiential learning and face-to-face interactions are key elements in settler decolonization.

Métodos de agrupamento hierárquico de textos são muito úteis para analisar o conhecimento embutido em coleções textuais, organizando os documentos textuais em grupos e subgrupos para facilitar a exploração do conhecimento em diversos níveis de granularidade. Tais métodos pertencem à área de aprendizado não supervisionado de máquina, uma que vez obtêm modelos de agrupamento apenas pela observação de regularidades existentes na coleção textual, sem supervisão humana. Os métodos tradicionais de agrupamento assumem que a coleção textual é representada apenas pela informação técnica, ou seja, palavras e frases extraídas diretamente dos textos. Por outro lado, em muitas tarefas de agrupamento existe conhecimento adicional e valioso a respeito dos dados, geralmente extraído por um processo avançado com apoio de usuários especialistas do domínio do problema. Devido ao alto custo para obtenção desses dados, esta informação adicional é definida como privilegiada e usualmente está disponível para representar apenas um subconjunto dos documentos textuais. Recentemente, um novo paradigma de aprendizado de máquina denominado LUPI (Learning Using Privileged Information) foi proposto por Vapnik para incorporar informação privilegiada em métodos aprendizado supervisionado. Neste trabalho de doutorado, o paradigma LUPI foi estendido para aprendizado não supervisionado, em especial, para agrupamento hierárquico de textos. Foram propostas e avaliadas abordagens para lidar com diferentes desafios existentes em tarefas de agrupamento, envolvendo a extração e estruturação da informação privilegiada e seu uso para refinar ou corrigir modelos de agrupamento. As abordagens propostas se mostraram eficazes em (i) consenso de agrupamentos, permitindo combinar diferentes representações e soluções de agrupamento; (ii) aprendizado de métricas, em que medidas de proximidades mais robustas foram obtidas com base na informação privilegiada; e (iii) seleção de modelos, em que a informação privilegiada é explorada para identificar relevantes estruturas de agrupamento hierárquico. Todas as abordagens apresentadas foram investigadas em um cenário de agrupamento incremental, permitindo seu uso em aplicações práticas caracterizadas pela necessidade de eficiência computacional e alta frequência de publicação de novo conhecimento textual. / Hierarchical text clustering methods are very useful to analyze the implicit knowledge in textual collections, enabling the organization of textual documents into clusters and subclusters to facilitate the knowledge browsing at various levels of granularity. Such methods are classified as unsupervised machine learning, since the clustering models are obtained only by observing regularities of textual data without human supervision. Traditional clustering methods assume that the text collection is represented only by the technical information, i.e., words and phrases extracted directly from the texts. On the other hand, in many text clustering tasks there is an additional and valuable knowledge about the problem domain, usually extracted by an advanced process with support of the domain experts. Due to the high cost of obtaining such expert knowledge, this additional information is defined as privileged and is usually available to represent only a subset of the textual documents. Recently, a new machine learning paradigm called LUPI (Learning Using Privileged Information) was proposed by Vapnik to incorporate privileged information into supervised learning methods. In this thesis, the LUPI paradigm was extended to unsupervised learning setting, in particular for hierarchical text clustering. We propose and evaluate approaches to deal with different challenges for clustering tasks, involving the extraction and structuring of privileged information and using this additional information to refine or correct clustering models. The proposed approaches were effective in (i) consensus clustering, allowing to combine different clustering solutions and textual representations; (ii) metric learning, in which more robust proximity measures are obtained from privileged information; and (iii) model selection, in which the privileged information is exploited to identify the relevant structures of hierarchical clustering. All the approaches presented in this thesis were investigated in an incremental clustering scenario, allowing its use in practical applications that require computational efficiency as well as deal with high frequency of publication of new textual knowledge.

This thesis explores swedes and the Swedish community in Paris as a diaspora and not simply as forming a temporary, touristic and fragmented stance. The case is set within the specific locality of Paris and considers the historic relationship between the two countries. This, alongside Frances’ policies towards immigration constitutes the context of the Swedish diaspora in Paris. Furthermore, the studied diaspora is viewed partly in relation to other diasporas in France, such as the African, the Kurdish, the Chinese and the Scottish – all facing different conditions as a diasporic group.  The material for this study was assembled through qualitative interviews and analysed with a qualitative content analysis approach. Furthermore, it was analysed in the light of diasporic and transnationalism theories. Through the analyses we see how swedes in Paris fulfil many of the criteria of a diasporic group which is featured in the theoretic literature. They have a dispersion, voluntary and touristic in its form with a focus on the new locality, a homeland orientation where the homeland serves as a present source for values and identity, and boundary-maintenance through a wide range of institutions and social connections. The members of the Swedish diaspora live transnational lives: present in, affected as well as being affected by, both Sweden and France simultaneously. Hence obtaining a form of transborder citizenship, although lacking a political focus. The analysis and discussion paint a picture of a privileged state bound diaspora without a political struggle. They enjoy a high rate of mobility and their ethnic heritage is viewed as an asset – hence no discrimination in the new homeland. The privilege entails the freedom characteristic of that of a nomadic diaspora. However, this nomadic state result in a certain degree of ambivalence and a sense of up rootedness, alongside the positive effects of being at home in two places at the same time. With its extensive mobility and flexibility, which sets it apart from other diasporas, the Swedish population in Paris form a different kind of nomadic and privileged diasporic unit.