L’équité est un concept large dont la signification et la richesse conceptuelle ont évolué temporellement au sein de la théorie du droit et de la théorie politique. Au travers d’une histoire de l’équité, partant de la conception d’Aristote jusqu’aux juristes réalistes américains, ce mémoire analyse et explique la transformation graduelle de ce concept dans le droit, dont la place fut tantôt au centre des réflexions autour de la justice, tantôt minimisée, voire écartée, mais jamais complètement supprimée. Nous fondant sur cette riche histoire de l’équité, nous reconnectons ce concept phare de la théorie du droit à une réception de celui-ci au sein de la théorie politique. Pour ce faire, nous mobilisons la théorie de la liberté comme non-domination de Philip Pettit comme le cadre d’une pratique contemporaine de l’équité, au travers de la jurisprudence de la Cour suprême du Canada sur l’équité procédurale. / The concept of “equity” is vast, and its meaning and depth have dramatically evolved over time within the political and legal theory fields. This thesis offers a history of the concept of equity, starting from Aristotle’s conception of justice and equity to the American legal realist movement. On that basis, this thesis analyzes and explains the reasons why such a gradual transformation of this concept happened and, therefore, how the role of equity changed from being at the centre of theories of justice and law to being minimized, almost excluded from the sphere of legal theory, but never completely suppressed. Drawing on this rich history of equity, we reconnect this key concept of legal theory with its reception in political theory. In that regard, we offer an account of Philip Pettit’s theory of freedom as non-domination understood as the framework for the contemporary practice of equity, notably through the example of the case law of the Supreme Court of Canada on procedural fairness.

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Local Law Enforcement and Immigration: Lessons and Recommendations from Police Executives (2007-2021) Tonya D. Chapman ABSTRACT The Immigration and Reform Control Act (IRCA) of 1986 and the Illegal Immigration Reform and Immigrant Responsibility Act of 1996 (IIRIRA) authorized the U.S. Immigration and Customs Enforcement agency (ICE) to enter into memoranda of agreement with local law enforcement under section 287(g). The 287(g) program includes the Task Force Model (TFM), Jail Enforcement Model (JEM), Secure Communities (SC), the Priority Enforcement Program (PEP) model and the Warrant Service Officer (WSO) Model, which authorizes specific responsibilities of immigration enforcement to local law enforcement agencies. This dissertation examines the impact of local law enforcement's participation in the various 287(g) programs from the perspective of law enforcement executives. Local law enforcement was granted the responsibility in part because Congress and local elected officials believed that immigration increased crime. However, as of 2022, little research on the nexus between crime and immigration supports that claim; nor does it support the claim that crime rates fell as a result of local law enforcement's participation in the 287(g) programs. Consistent with prior research, this dissertation finds that immigration enforcement has a "null or non-significant" effect on crime in these jurisdictions in comparison to jurisdictions that did not participate in the 287(g) programs. Moreover, this dissertation shows that law enforcement's participation in immigration enforcement led to unintended consequences, including adverse impacts on police legitimacy (trust and fear), perceived crime reporting by immigrant communities, and their community policing efforts. This research provides guidance on best practices to law enforcement in an effort to re-imagine the profession in accordance with procedural justice principles. It examines whether and how immigration enforcement has posed challenges for building trust, legitimacy, community engagement and transparency for law enforcement; looks at whether federal mandates and immigration enforcement affected the advancement of community policing and procedural justice; provides insight on lessons learned from law enforcement's perspective; and contributes to research on the immigration-crime nexus. / Doctor of Philosophy / Local Law Enforcement and Immigration: Lessons and Recommendations from Police Executives (2007-2021) Tonya D. Chapman GENERAL AUDIENCE ABSTRACT Section 287(g) under the Immigration and Reform Control Act (IRCA) of 1986 and the Illegal Immigration Reform and Immigrant Responsibility Act of 1996 (IIRIRA) authorized the U.S. Immigration and Customs Enforcement agency (ICE) to enter into memoranda of agreement with local law enforcement agencies to participate in immigration enforcement. Under Section 287(g), ICE implemented 5 programs, including the Task Force Model (TFM), Jail Enforcement Model (JEM), Secure Communities (SC), the Priority Enforcement Program (PEP) model, and the Warrant Service Officer (WSO) model. This dissertation examines the impact of local law enforcement's participation in the 287(g) programs, from the perspective of law enforcement executives. This dissertation shows that law enforcement's participation in immigration enforcement led to unintended consequences, including adverse impacts on police legitimacy (trust and fear), perceived crime reporting by immigrant communities, and their community policing efforts. The dissertation also finds that immigration enforcement has a "null or non-significant" effect on crime. This research provides guidance on best practices to law enforcement in an effort to re-imagine the profession in accordance with fair and impartial policing principles.

Driven by the surging need for seamless connectivity, research in the wireless communication area has dramatically evolved over the years to meet the increasing demand for data rate and seamless coverage. Such evolvement concurs with a notable increase in data traffic and the widespread of data-hungry devices, thereby inflicting stringent requirements on terrestrial networks. Despite the tremendous advances achieved through the past generations of wireless systems, almost half of the world's population remains unconnected, leading to an accentuated digital divide problem. Therefore, this work invigorates a new connectivity solution that integrates aerial and terrestrial communications with a high-altitude platform station (HAPS) to promote a sustainable connectivity landscape. The connectivity solution adopted in this thesis specifically integrates terrestrial base stations with hot-air balloons under the framework of a cloud-enabled HAPS via a data-sharing fronthauling strategy. The aerial (hot-air balloons) and terrestrial base stations, grouped into disjoint clusters, coordinate their mutual transmission to serve aerial (i.e., drones) and terrestrial users. This work studies the downlink communication from the cloud-enabled HAPS to the aerial and terrestrial users under practical system considerations, namely the limited transmit power and the limited-capacity fronthaul link, per-base station. To this end, the first part of the thesis devises a specific optimization problem that maximizes the network sum-rate while accounting for system design constraints to determine the user association strategy, i.e., user to terrestrial clusters or user to air clusters, and the associated beamforming vectors. The second part of the thesis, then, designs a different resource allocations optimization problem that accounts for the fairness among the users, thus adopting a proportionally fair scheduling scheme to assign users on frequency tones to maximize the log of the long-term average rate. On this account, the work solves a handful of non-convex intricate optimization problems using techniques from optimization theory, namely, fractional programming and $\ell_0$-norm approximation. The work consequently outlines the gains realized by providing on-demand coverage in crowded and unserved areas. Moreover, the thesis illustrates the benefits of coordinating the operations of aerial and terrestrial base stations for interference management, load-balancing, and fairness measures.

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To solve the bottleneck problem of resource utilization and user experience quality in mobile communication networks, 5G introduces network slicing to cope with the huge resource demand of users. To further improve the quality of service for users with different needs, a new fairness definition based on service level objective is introduced. On this basis, a network slicing dynamic resource scheduling strategy based on the greedy algorithm is designed, and the actual application scenarios of slicing scheduling and user scheduling are simplified into a two-layer model, namely the slicing-user model, and combined with the greedy algorithm to make the service weight value. Combine the largest slice and the user with the highest priority, and complete the matching service. The advantage of this method is various system resources can be fairly allocated according to the same proportion to users. Through the optimal combination of each slice and user, the resources of the entire system can be fairly allocated to users with different needs. Python simulation results showed that the newly proposed network slicing dynamic resource scheduling mechanism based on the greedy algorithm can meet the different needs of users and achieve short term fairness, where the users get a fair share of the resource by each missing their SLO by a similar percentage, so as to better meet the needs of users. / För att lösa flaskhalsproblemet med resursanvändning och användarupplevelsekvalitet i mobilkommunikationsnät introducerar 5G nätverksskivning för att klara användarnas enorma resursbehov. För att ytterligare förbättra servicekvaliteten för användare med olika behov införs en ny rättvisedefinition baserad på servicenivåmål. På grundval av detta utformas en dynamisk resursplaneringsstrategi för nätverksskivning baserad på den giriga algoritmen, och de faktiska applikationsscenarierna för skivningsplanering och användarschemaläggning förenklas till en tvåskiktsmodell, nämligen skivningsanvändarmodellen, och kombineras med girig algoritm för att göra tjänstens viktvärde. Kombinera den största delen och användaren med högsta prioritet och slutför motsvarande tjänst. Fördelen med denna metod är att olika systemresurser kan fördelas rättvist enligt samma andel, och genom den bästa kombinationen av varje segment och användare kan hela systemets resurser fördelas rättvist till användare med olika behov. Pythons simuleringsresultat visar att den nyligen föreslagna nätverksskärningsdynamiska resursplaneringsmekanismen baserad på den giriga algoritmen kan tillgodose användarnas olika behov och uppnå kortsiktig rättvisa där användarna får en rättvis andel av resursen genom att var och en saknar sin SLO med en liknande procentsats , för att bättre möta användarnas behov.

AI has quickly grown from being a vast concept to an emerging technology that many companies are looking to integrate into their businesses, generally considered an ongoing “revolution” transforming science and society altogether. Researchers and organizations agree that AI and the recent rapid developments in machine learning carry huge potential benefits. At the same time, there is an increasing worry that ethical challenges are not being addressed in the design and implementation of AI systems. As a result, AI has sparked a debate about what principles and values should guide its development and use. However, there is a lack of consensus about what values and principles should guide the development, as well as what practical tools should be used to translate such principles into practice. Although researchers, organizations and authorities have proposed tools and strategies for working with ethical AI within organizations, there is a lack of a holistic perspective, tying together the tools and strategies proposed in ethical, technical and organizational discourses. The thesis aims to contribute with knowledge to bridge this gap by addressing the following purpose: to explore and present the different tools and methods companies and organizations should have in order to build machine learning applications in a fair and transparent manner. The study is of qualitative nature and data collection was conducted through a literature review and interviews with subject matter experts. In our findings, we present a number of tools and methods to increase fairness and transparency. Our findings also show that companies should work with a combination of tools and methods, both outside and inside the development process, as well as in different stages of the machine learning development process. Tools used outside the development process, such as ethical guidelines, appointed roles, workshops and trainings, have positive effects on alignment, engagement and knowledge while providing valuable opportunities for improvement. Furthermore, the findings suggest that it is crucial to translate high-level values into low-level requirements that are measurable and can be evaluated against. We propose a number of pre-model, in-model and post-model techniques that companies can and should implement in each other to increase fairness and transparency in their machine learning systems. / AI har snabbt vuxit från att vara ett vagt koncept till en ny teknik som många företag vill eller är i färd med att implementera. Forskare och organisationer är överens om att AI och utvecklingen inom maskininlärning har enorma potentiella fördelar. Samtidigt finns det en ökande oro för att utformningen och implementeringen av AI-system inte tar de etiska riskerna i beaktning. Detta har triggat en debatt kring vilka principer och värderingar som bör vägleda AI i dess utveckling och användning. Det saknas enighet kring vilka värderingar och principer som bör vägleda AI-utvecklingen, men också kring vilka praktiska verktyg som skall användas för att implementera dessa principer i praktiken. Trots att forskare, organisationer och myndigheter har föreslagit verktyg och strategier för att arbeta med etiskt AI inom organisationer, saknas ett helhetsperspektiv som binder samman de verktyg och strategier som föreslås i etiska, tekniska och organisatoriska diskurser. Rapporten syftar till överbrygga detta gap med följande syfte: att utforska och presentera olika verktyg och metoder som företag och organisationer bör ha för att bygga maskininlärningsapplikationer på ett rättvist och transparent sätt. Studien är av kvalitativ karaktär och datainsamlingen genomfördes genom en litteraturstudie och intervjuer med ämnesexperter från forskning och näringsliv. I våra resultat presenteras ett antal verktyg och metoder för att öka rättvisa och transparens i maskininlärningssystem. Våra resultat visar också att företag bör arbeta med en kombination av verktyg och metoder, både utanför och inuti utvecklingsprocessen men också i olika stadier i utvecklingsprocessen. Verktyg utanför utvecklingsprocessen så som etiska riktlinjer, utsedda roller, workshops och utbildningar har positiva effekter på engagemang och kunskap samtidigt som de ger värdefulla möjligheter till förbättringar. Dessutom indikerar resultaten att det är kritiskt att principer på hög nivå översätts till mätbara kravspecifikationer. Vi föreslår ett antal verktyg i pre-model, in-model och post-model som företag och organisationer kan implementera för att öka rättvisa och transparens i sina maskininlärningssystem.

The thesis focuses on the way the secondary students of an international British curriculum school in Spain portray gender equality. It analyses the themes emerging from a focus group discussion with a close consideration of the concepts of gender, gender equality, and gender mainstreaming. A crucial element underpinning the research is the concept of children’s voices, as the study aims at creating space for those voices to be expressed and heard. This paper addresses various notions constituting inextricable parts of the identified themes: the notions of fairness, responsibility, control, and heteronormativity. I argue that this kind of research is a necessity due to insufficient consideration of children’s voices in policy-making processes in education. I denounce the paucity of adults’ knowledge of school children’s needs and opinions. This paper aims at understanding how students define gender equality, how they associate it with the notions of responsibility, control and fairness, and how my assumptions, as an adult and as a teacher, differ from the perception of secondary students in question.

No / People, systems, and things in the cities generate large amount of data which is considered to be the most scalable asset of any smart city. Linux users are rapidly increased in last few years, and many large multinational organizations are deploying long distance high bandwidth (LDHB) cloud networks for centralizing the data from various smart cities on a central location. TCP is responsible for reliable communication of data in these cloud networks. For reliability communication among various smart cities, a number of TCP congestion control mechanisms have been developed in the past. TCP Compound, TCP Fusion, and TCP CUBIC are the default TCP congestion control mechanisms for Microsoft Windows, Sun Solaris, and Linux operating systems respectively. The response function of TCP CUBIC is higher than the response function of Standard TCP, which is a trademark congestion control mechanism. As a result, TCP CUBIC does not behave friendly with Standard TCP in LDHB cloud networks. The Congestion Window (cwnd) reduction and growth of TCP CUBIC is very aggressive, which causes high packet loss rate and unfair share of available link bandwidth among competing flows from various smart cities. The aim of this research is to design a new TCP congestion control mechanism for Linux operating system to achieve maximum performance in LDHB cloud networks being used by smart cities. In this paper, congestion control module for slow start (CCM-SS) is designed by increasing the lower boundary limit of cwnd size in slow start phase of communication. Congestion control module for loss event (CCM-LE) is designed by increasing the cwnd reduction rate at each packet loss event and finally Advance Response Function for TCP CUBIC (ARFC) is proposed to design a new congestion control mechanism for Linux operating system. NS-2 is used to compare the performance of TCP CUBIC* with TCP CUBIC in short distance high bandwidth (SDHB) and long distance high bandwidth (LDHB) cloud networks. Results show that TCP CUBIC* has outperformed in LDHB networks, at least by a factor of 18% as compared to TCP CUBIC.