Law Commons^™

Dispute Settlement Under The African Continental Free Trade Area Agreement: A Preliminary Assessment, Olabisi D. Akinkugbe

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The African Continental Free Trade Area Agreement (AfCFTA) will add a new dispute settlement system to the plethora of judicial mechanisms designed to resolve trade disputes in Africa. Against the discontent of Member States and limited impact the existing highly legalized trade dispute settlement mechanisms have had on regional economic integration in Africa, this paper undertakes a preliminary assessment of the AfCFTA Dispute Settlement Mechanism (DSM). In particular, the paper situates the AfCFTA-DSM in the overall discontent and unsupportive practices of African States with highly legalized dispute settlement systems and similar WTO-Styled DSMs among other shortcomings. Notwithstanding the transplantation of …

Nil/Tu,O Child And Family Services Society V. B.C. Government And Service Employees’ Union’ And Communications, Energy And Paperworkers Union Of Canada V. Native Child And Family Services Of Toronto, Naiomi Metallic

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In NIL/TU,O and Native Child, the Supreme Court of Canada held that unions applying for certification to represent employees of Indigenous-run child and family agencies ought to be certified under provincial labour relations legislation. The majority in both cases applied a presumptive rule that labour relations are generally provincial matters. This presumption was not displaced by the fact that both agencies were Indigenous-run organizations. The Indigenous nature of the organizations, their clientele, staff, and governance, or their own preferences for labour regimes made no difference to the Court’s analysis.

Held: Appeals Allowed.

1.

The appeals should be allowed. Treating Indigenous …

Legal Risks Of Adversarial Machine Learning Research, Ram Shankar Siva Kumar, Jonathon Penney, Bruce Schneier, Kendra Albert

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Adversarial machine learning is the systematic study of how motivated adversaries can compromise the confidentiality, integrity, and availability of machine learning (ML) systems through targeted or blanket attacks. The problem of attacking ML systems is so prevalent that CERT, the federally funded research and development center tasked with studying attacks, issued a broad vulnerability note on how most ML classifiers are vulnerable to adversarial manipulation. Google, IBM, Facebook, and Microsoft have committed to investing in securing machine learning systems. The US and EU are likewise putting security and safety of AI systems as a top priority.

Now, research on adversarial …

An Examination Of How The Canadian Military’S Legal System Responds To Sexual Assault, Elaine Craig

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Although the Canadian military has been conducting sexual assault trials for over twenty years, there has been no academic study of them and no external review of them. This review of the military’s sexual assault cases (the first of its kind) yields several important findings. First, the conviction rate for the offence of sexual assault by courts martial is dramatically lower than the rate in Canada’s civilian criminal courts. The difference between acquittal rates in sexual assault cases in these two systems appears to be even larger. Since Operation Honour was launched in 2015 only one soldier has been convicted …