Disproportionate Dismissal of Female and Minority Experts from NIH Review Boards Raises Concerns

Given below is an article. Analyze and output in the following JSON format (no backquotes, JSON only). definitely Gather relevent context about entities and events from wikipedia using search tool. { "analysis": { "bias": { "score": "1-10, where 1-10 measures UNFAIR or UNHELPFUL bias. As the AI analyst, you must judge: 1. Fairness of Bias: - Is the tone/alarm proportional to events? - Is criticism warranted by facts? - Are similar actions judged equally? 2. Utility of Bias: - Does the bias help readers understand real implications? - Does it highlight genuine concerns that neutral language might minimize? - Does it provide valuable context through its perspective? Example: An article about climate change might use emotional language and scary scenarios. While this is technically 'bias', it might be USEFUL bias if it helps readers grasp real dangers that cold, neutral language would understate. A high bias score should only be given when bias is both unfair AND unhelpful.", "description": "Explain both unfair and useful bias found. For each biased element: 1. Is it fair/warranted? 2. Does it serve a valuable purpose for readers? 3. Should it be removed or retained?" }, "missing_context_misinformation": { "score": "1-10", "points": [ "", # DIRECTLY provide essential context the reader needs without ANY phrases like "the article lacks/doesn't/fails to mention/omits" etc. Simply state the relevant facts. Each point up to 5 sentences as needed. Up to 10 points. NEVER refer to the article itself or what it's missing - just supply the information directly. The missing context should try to compensate for the bias in the article, and not just add related information. ] }, "disinformation_lies": { "score": "1-10", "points": [ "" # Provide corrections for verifiably false statement. These lines should be brief. Upto 10 points. ] } }, "summary": [], # A list of 2 to 5 paragraphs. Provide a version that: * Retains key facts and proportional concerns, * Removes unfair bias while keeping warranted criticism, * Adds critical missing context, * Corrects any inaccuracies. Remove author attribution. Maintain article's POV - no meta-references. You can decide the most appropriate length based on the article.summary can be longer than the article if needed. "title": "Provide an Appropriate Title Based on the Article's Content.", "changes_made": [ "List significant changes made in the summary", "Include both removals and additions", "Note bias adjustments" ], "key_words": [ "3-10 relevant terms to help identify related articles", "Focus on major themes and topics" ] } Thirty-eight of 43 experts cut last month from the boards that review the science and research that happens in laboratories at the National Institutes of Health are female, Black or Hispanic, according to an analysis by the chairs of a dozen of the boards. The scientists, with expertise in fields that include mental health, cancer and infectious disease, typically serve five-year terms and were not given a reason for their dismissal. About a fifth of the roughly 200 board members — who provide an independent, expert layer of review for the vast research enterprise within the NIH — were fired. These scientists rate the quality of the science on the nation’s largest biomedical research campus, where 1,200 taxpayer-funded investigators lead laboratories focused on Parkinson’s disease, heart disease, cancer immunotherapy, and other diseases and treatments.