Social Network Analysis

Sweeney, Patricia M.; Bjerke, Elizabeth; Güçlü, Hasan; Keane, Christopher; Galvan, Jared; Gleason, Sherrianne M.; Potter, Margaret A.

doi:10.1097/phh.0b013e31829fc013

Cited by 5 publications

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They use the codes to generate, analyze and compare network diagrams representing various functional features of states' regulatory frameworks for public health emergency preparedness. As described more fully in Sweeney et al (2013), they retrieved candidate sets of relevant statutes and regulations from a full-text legal information service and identified relevant spans of text. They then coded the relevant spans as per instructions in the codebook, representing relevant features of those spans as sequences of numerical codes.…”

Section: Phasys Statutes and Regulations Analysismentioning

confidence: 99%

The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts

Savelka,

Ashley

2023

Front. Artif. Intell.

View full text Add to dashboard Cite

The emergence of ChatGPT has sensitized the general public, including the legal profession, to large language models' (LLMs) potential uses (e.g., document drafting, question answering, and summarization). Although recent studies have shown how well the technology performs in diverse semantic annotation tasks focused on legal texts, an influx of newer, more capable (GPT-4) or cost-effective (GPT-3.5-turbo) models requires another analysis. This paper addresses recent developments in the ability of LLMs to semantically annotate legal texts in zero-shot learning settings. Given the transition to mature generative AI systems, we examine the performance of GPT-4 and GPT-3.5-turbo(-16k), comparing it to the previous generation of GPT models, on three legal text annotation tasks involving diverse documents such as adjudicatory opinions, contractual clauses, or statutory provisions. We also compare the models' performance and cost to better understand the trade-offs. We found that the GPT-4 model clearly outperforms the GPT-3.5 models on two of the three tasks. The cost-effective GPT-3.5-turbo matches the performance of the 20× more expensive text-davinci-003 model. While one can annotate multiple data points within a single prompt, the performance degrades as the size of the batch increases. This work provides valuable information relevant for many practical applications (e.g., in contract review) and research projects (e.g., in empirical legal studies). Legal scholars and practicing lawyers alike can leverage these findings to guide their decisions in integrating LLMs in a wide range of workflows involving semantic annotation of legal texts.

show abstract

Section: Phasys Statutes and Regulations Analysismentioning

confidence: 99%

The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts

Savelka,

Ashley

2023

Front. Artif. Intell.

View full text Add to dashboard Cite

show abstract

Lake and the laws: An exploratory network analysis of legal provisions for lake management

Irawan

2021

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Integrated lake management requires coherence of various regulations related to environmental preservation and natural resource use. There are, as of yet, no specific laws governing lake management. Legal provisions related to lake management are widely scattered in various environmental legislations. Legal provisions provide a framework for stakeholders, especially government agencies, to take the various actions required in lake management and have a major impact on the efficiency and effectiveness of implementing these measures. This study aims to analyse the relationship between various legal provisions of lake management as mandated in laws and regulations. The method used in this research is exploratory quantitative method by applying social network analysis tools. The data used are 32 laws and government regulations identified have relevance to lake management. The analysis shows that the legal provisions of lake management in Indonesia are complex and tend to be sectoral. The complexity on the one hand gives an indication that the management of the lake has been arranged in detail and on the other hand shows the neglect of complexity and ambiguity in implementation. Weak law enforcement also adds to the problem of implementation. The implication of these findings is the need for government efforts to synchronize various regulations in lake management.

show abstract

Preparedness and Emergency Response Research Centers: Using a Public Health Systems Approach to Improve All-Hazards Preparedness and Response

2014

View full text Add to dashboard Cite

In 2008, at the request of the Centers for Disease Control and Prevention (CDC), the Institute of Medicine (IOM) prepared a report identifying knowledge gaps in public health systems preparedness and emergency response and recommending near-term priority research areas. In accordance with the Pandemic and All-Hazards Preparedness Act mandating new public health systems research for preparedness and emergency response, CDC provided competitive awards establishing nine Preparedness and Emergency Response Research Centers (PERRCs) in accredited U.S. schools of public health. The PERRCs conducted research in four IOM-recommended priority areas: (1) enhancing the usefulness of public health preparedness and response (PHPR) training, (2) creating and maintaining sustainable preparedness and response systems, (3) improving PHPR communications, and (4) identifying evaluation criteria and metrics to improve PHPR for all hazards. The PERRCs worked closely with state and local public health, community partners, and advisory committees to produce practice-relevant research findings. PERRC research has generated more than 130 peer-reviewed publications and nearly 80 practice and policy tools and recommendations with the potential to significantly enhance our nation's PHPR to all hazards and that highlight the need for further improvements in public health systems.

show abstract

Social Network Analysis

Cited by 5 publications

References 6 publications

The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts

The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts

Lake and the laws: An exploratory network analysis of legal provisions for lake management

Preparedness and Emergency Response Research Centers: Using a Public Health Systems Approach to Improve All-Hazards Preparedness and Response

Contact Info

Product

Resources

About