[{"source":"Canadian Association of Law Libraries / L'Association canadienne des bibliothèques de droit CALL/ACBD Blog","description":"From time to time, this blog will highlight initiatives, ideas, or activities coming from members, committees or special interest groups (SIGs). Today: Adapting the SALI Taxonomy to the Canadian Legal Environment , b y Michael McAlpine , Manager, Information, Research & Knowledge at Siskinds (London, Ontario) On September 28 th , the Knowledge Management Special Interest Group of CALL met to discuss and learn about the Legal Matter Specification Standard developed by the SALI Alliance . The SALI Alliance (Standards Advancement for the Legal Industry) is a non-profit organization open to all stakeholders in the legal community. Members include law firms, companies, legal service providers, legal industry associations and academic institutions. Founding sponsors are the Legal Marketing Association (LMA) and the Association of Legal Administrators (ALA). Guest speaker Jim Hannigan spoke about the history of the taxonomy and the current uses of it in the legal industry. Michael McAlpine then discussed the work done by the SALI Canadian Working Group to adapt the taxonomy to the Canadian legal environment . There was a general discussion about the uses of the taxonomy and efforts to implement it in law firms. First released in 2019, the SALI taxonomy was developed in order to provide a standard method for describing legal matters and associated documents. Version 2.0 was released at the end of 2020 and represented a significant expansion of the code set. Organizations and individuals around the globe continue to contribute to its development and growth. The SALI taxonomy is extensible and can work in conjunction with other standards (eg, NAICS, UTBMS codes). SALI is an open, free and party neutral that can be used by law firms, vendors and others in the legal industry to ensure matters and documents are described consistently. SALI has been endorsed by several large law firms and by vendors such as Fastcase, NetDocuments and Reynen Court. Some of the core attributes of the current standard are: Area of Law: Each matter can be assigned a primary and secondary area of law. Primary areas include topics such as Corporate Law, Constitutional and Human Rights, Personal and Family Law, and Food and Drug Law. Secondary areas are more specific and include topics such as Corporate Governance, Accident Benefits Law, and Labour Law. Service: The Services attribute is a central feature of the taxonomy. Examples of services are Transaction, Advisory, or Dispute. Services provide more detail to a matter description than just relying solely on Area of Law. Player Role: The Role attribute is what makes SALI party neutral. Roles include Appellant, Respondent, Acquiror or Acquiree. Other attributes that can be used to describe a matter or client include Industry, Legal Entity, Location, or Trial Type. The KM SIG will next meet on November 30 th to discuss website monitoring applications. If you would like an invitation, please contact Michael","id":3241454,"url":"https://www.callacbd.ca/CALL-Blog/12098999","titre":"Adapting the SALI Legal Taxonomy to the Canadian Environment","pubDate":"Mon, 26 Oct 2026 07:55:47 +0100"},{"url":"https://www.callacbd.ca/CALL-Blog/11129241","titre":"Diversity, Inclusion, and Decolonization Committee Events on Truth and Reconciliation between Indigenous and non-Indigenous Peoples","pubDate":"Mon, 26 Oct 2026 07:55:46 +0100","source":"Canadian Association of Law Libraries / L'Association canadienne des bibliothèques de droit CALL/ACBD Blog","description":"September 30 has been a significant date in Canada since 2013, when Phyllis Webstad from the Stswecem’c Xgat’tem First Nation shared her story of attending St. Joseph’s Residential School in Williams Lake, BC, for the first time in 1973. As a youngster , she proudly wore her shiny new orange shirt, only to have it taken from her by the school. Since then, Orange Shirt Day has been a national movement in Canada where people across the country wear orange in honour of Phyllis and other residential school survivors, so that we both recognize and raise awareness of the history and legacies of the Canadian residential school system. This year’s Orange Shirt Day, September 30, 2021, is also the inaugural National Day for Truth and Reconciliation in Canada. As part of its mandate, the Diversity, Inclusion, and Decolonization Committee (DIDC) of CALL/ACBD is committed to fostering awareness and acumen in respect of issues of diversity, inclusion, and decolonization within all sectors of law librarianship and related professions. Truth and Reconciliation between Indigenous and non-Indigenous peoples is a national movement that is not only limited to one day, but is an ongoing effort so that Indigenous Peoples and their rights are recognized, understood and respected by all . In this spirit, the DIDC, as part of CALL/ACBD, would like to highlight a couple of upcoming opportunities available to all of us to bring together our colleagues in order to honour survivors, their families and communities, and to sadly remember those who didn’t make it home: On Thursday, September 30 , the University of Windsor Law Library will be hosting WAAYDANAA | Now is the Time . The event will be held virtually and is free. Registration is required . Nadine Hoffman, in coordination with the Academic SIG and the DIDC, is planning a related event on strategies for aspects of Indigenous research to help us better understand legal research in relation to Indigenous Peoples. Stay tuned – format and details to","id":3241451},{"titre":"The (Currently) Uneven Intelligence of AI in Comparative Constitutional Law","url":"https://verfassungsblog.de/the-currently-uneven-intelligence-of-ai-in-comparative-constitutional-law/","pubDate":"Thu, 15 Oct 2026 08:26:22 +0200","source":"Scoop.it - Documentation juridique (Stéphan Cottin)","description":"This article belongs to the debate » Thinking Machines, Thinking Lawyers14 October 2026The (Currently) Uneven Intelligence of AI in Comparative Constitutional Law From Years of Research to a Single Prompt? Artificial intelligence (AI) has the potential to accelerate and improve the quality of research. This potential has inspired numerous projects exploring how AI could help scholarship on constitutional law. For example, there is research using AI to interpret constitutions,1) apply constitutional principles,2) and predict court rulings.3) Even the question of whether AI could improve the process of constitution-making has been studied.4) AI’s potential is particularly significant for comparative constitutional research. Systematically comparing legal systems requires locating sources from different jurisdictions, which are often difficult to access and only available in local languages. The creation of comparative legal datasets has thus involved considerable personnel, time, and financial resources. AI can overcome many of these obstacles. AI models can search for and translate foreign-language sources, filter them, and convert the filtered information into a dataset. In doing so, AI offers the prospect of datasets — which previously required years of research and the efforts of numerous experts and research assistants to compile — being just a prompt away. However, whether AI models can generate comparative law datasets that are qualitatively comparable to human-coded datasets has not yet been addressed (although Guha et al provide an example for a broader legal benchmarking exercise).5) We therefore conducted our own benchmarking study.6) We found evidence suggesting that recent AI models may be able to code simple factual data, but they are likely unreliable substitutes for expert human coders when conceptual or interpretive judgment is required. The Benchmarking Project: Seven Coding Tasks, Four Datasets, Two LLMs In our project, we tested the ability of two large language models (LLMs) to code different types of information relevant to comparative constitutional law. We specifically assessed whether LLMs can reproduce information from four existing comparative constitutional law datasets, all of which were compiled through human coding and which served as a ‘ground truth’ for our exercise. From these datasets, we asked the LLMs to code seven variables, which can be thought of as seven tasks relevant to the creation of comparative constitutional law datasets. Each of these tasks is either a test of fact-finding or reasoning abilities. First, from the Executive Term Limit Evasion Dataset,7) we drew information on whether presidents in 106 presidential systems have evaded constitutionally mandated term limits between 2000 and 2019. The dataset includes one variable on whether presidents attempt to overstay past the end of their term. The second variable captures what strategies executives use for doing so, such as amending the constitution, replacing it with a new one, or asking the court to interpret term limits out of the constitution. While determining whether a president overstayed is a fact-finding task, assessing the strategy used to do so requires reasoning. Second, from the Comparative Constitution Making Dataset,8) we drew information on the process by which constitutions were adopted in democracies between 1900 and 2015. This dataset also includes fact-finding variables such as (1) whether citizens were involved in the formulation, discussion, or submission of reform proposals, and (2) whether citizens participated in popular referendums at any stage in the process. The dataset’s most important variable (3) captures whether constitutions reflect ‘plural elite agreement,’ that is, whether all relevant elite factions in society were involved and represented during the process. The recreation of this variable requires reasoning. Third, from the Characteristics of National Constitutions Dataset9), we drew on its coding of 43 first-generation constitutional","id":3218421},{"source":"Blog d'Arthur Perret","id":3047509,"description":"This paper reports on an experiment which connects document design with document theory. Document design is about what documents should do. We use the example of document graphs and of Cosma, a visualization program created during the HyperOtlet research programme, to show how theory can inform design decisions and help conceptualize results. This paper is currently under peer review.