[{"titre":"FDA Proposes Rule to Update Infant Formula Nutrient Requirements","id":3251756,"pubDate":"Fri, 30 Oct 2026 07:53:31 +0100","description":"Today, the U.S. Department of Health and Human Services (HHS) and the Food and Drug Administration (FDA) issued the first of three proposed rules that aim to update infant formula nutrient requirements. While the formal rulemaking process commences, FDA has also released new chemical contaminant testing data demonstrating that most infant formula samples showed low or non-detectable levels of contaminants, according to HHS' press release . FDA intends to conduct a comprehensive review of the 30 nutrients currently required in infant formula marketed in the United States. The FDA intends to consolidate final changes to infant formula nutrient requirements into a single comprehensive final rule. Today's proposed rule (phase 1 of three) would update requirements for iodine, manganese, vitamin A, and vitamin D and reaffirm existing requirements for chloride, potassium, selenium, and sodium. It would also change the units of measure for two nutrients and request public input on potential requirements for ingredients that are currently not required in infant formula but commonly added by manufacturers due to their nutritional value ( e.g ., arachidonic acid (ARA), docosahexaenoic acid (DHA), and L-carnitine). FDA is accepting comments on the proposed rule until February 26, 2027. Keller and Heckman LLP will provide updates throughout the rulemaking","source":"The Daily Intake","url":"https://www.dailyintakeblog.com/2026/10/fda-proposes-rule-to-update-infant-formula-nutrient-requirements/"},{"id":3232003,"pubDate":"Wed, 21 Oct 2026 14:33:39 +0200","titre":"The Old Québec (Vieux-Québec) historic district: Heritage, tourism and real-estate developers since the post-war years","description":"Introduction There are several ways of conceiving heritage conservation. For the purpose of this paper, we need to start from the premise that what we call “heritage” is a dynamic, evolving reality, and that a historic district such as “Old Québec” can undergo structuring transformations rooted in a process of heritage conservation. In Old Québec, the process of conservation —also referred to “patrimonialization”—has not received the attention it deserves. This paper aims to shed light on the process of functional requalification has undergone by Old Québec since the 1950s, within the broader context of its transformation into a historic district. It is based on discourse analysis (Berthold, 2013), supported by a diversifie body of documentation, including primary sources, such as archival documents, press reviews, geospatial and land-use data, and official reports. It is complemented by a body of scholarly literature devoted to Old Québec since the 1970s. First, we explain the sociohistorical process that led to the creation of Old Québec, starting in the 1950s. Then, we highlight the role played by tourism and the real-estate economy —includingdevelopers—in this process. Turning the Champlain District into a historic district At the turn of the 1950s, the area now known as “Old Québec” was referred to as the Champlain District. Named after the city’s main colonial founder, Champlain was one of the first areas to be settled, beginning in the early 17th century. It covers","url":"https://www.cahiers-espi2r.fr/2305","source":"ESPI2R"},{"url":"https://verfassungsblog.de/the-currently-uneven-intelligence-of-ai-in-comparative-constitutional-law/","source":"Scoop.it - Documentation juridique (Stéphan Cottin)","pubDate":"Thu, 15 Oct 2026 08:26:22 +0200","id":3218421,"titre":"The (Currently) Uneven Intelligence of AI in Comparative Constitutional Law","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"},{"source":"FTC USA Business Blog Posts","url":"https://www.ftc.gov/business-guidance/blog/2016/06/practice-fusion-case-suggests-6-health-privacy-pointers","titre":"Practice Fusion case suggests 6 health privacy pointers","pubDate":"Sat, 03 Oct 2026 08:09:37 +0200","id":3194910,"description":"Practice Fusion case suggests 6 health privacy pointers lfair June 8, 2016 | 9:01AM Practice Fusion case suggests 6 health privacy pointers By Lesley Fair Combine two of the most talked-about consumer protection topics – health privacy and consumer-generated online content – and what do you get? A proposed FTC settlement with Practice Fusion, the largest cloud-based electronic health records company in the country, and six compliance tips for others in the industry. One of San Francisco-based Practice Fusion’s primary products is an electronic records system for outpatient providers. In 2009, the company launched “Patient Fusion,” an online portal where patients whose providers were already using Practice Fusion could view or download their health information or transmit it to another provider. Patient Fusion also let patients send and receive secure messages from their providers. Fast forward several years and the company decided to expand Patient Fusion to include a public directory where current and prospective enrollees could search for doctors geographically or by specialty, read patient reviews of providers, and request appointments. But Practice Fusion had to ask itself a question familiar to many online companies: How do we get the content – in this case, patient reviews? That’s the focus of the FTC’s lawsuit. According to the complaint , Practice Fusion solicited data in a misleading way that led some patients to believe they were sending follow-up messages directly to their doctors about their diagnosis, medical treatment, prescriptions, etc. – and not contributing content to a public website. Practice Fusion, however, populated its new site with the information those people provided, some of which was highly sensitive. Here’s what happened. After appointments with their doctors, patients received emails titled “How was your visit?” The message continued, “To help improve your service in the future, please let us know how your visit went” and included a link with rating stars. The message ended this way: Thank you, Dr. [Name] In a footer, the message said “This email was sent to you by Patient Fusion®, a tool Doctor [Name] uses to deliver the highest quality of care to patients.” Below that in smaller print it said “Sent on behalf of Doctor [Name]’s office by: Practice Fusion.” If patients clicked the link, they were taken to a page that asked for feedback about things like how long they had to wait for their appointment, the doctor’s bedside manner, and whether their medical concern was addressed. There also was a text box where patients were invited to “leave a review for your provider.” Below that was a pre-checked box with the phrase “Keep this review anonymous.” What did some people put in that box? Highly sensitive information directly addressed to their doctors, not evaluations meant to be shared publicly. Here are just a few examples: “Dr [name], My Xanax prescription that I received on Monday was for 1 tablet a day but usually it’s for 2 tablets a day. I have not taken it to the pharmacy yet. Can I pick up a new one, or can I get a prescription called into a pharmacy? Thanks, [patient’s full name] “I called today and left a message regarding my daughter and no one has returned my call. I think she is depressed and has stated several times this week that she wishes she was dead. Could someone please call me [phone number]?” “The cefuroxime axetil does not seem to be doing anything for me. I did a little research and I think I have a yeast infection called candida. Not sure what to do about it yet. I guess I will first try to change my diet. Medication? [patient’s full name] “I would like to make an appointment for my back pain and possible shingles. Can you please call me @ [phone number]? Thank you! [patient's full name]” “I HAVE NO INFECTION [healthcare provider name]. EVERYTHING WENT"},{"url":"https://www.arthurperret.fr/blog/2023-11-01-document-theory-and-document-design.html","source":"Blog d'Arthur Perret","pubDate":"Thu, 23 Jul 2026 10:17:34 +0200","id":3047509,"titre":"[Article] Document theory and document design","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.