Adding Statute Links Where There Were None

Great tip from RIPS Law Librarian blog  on a tool for pulling the text of statutes from a web page that fails to include the hypertext link (link here). The tool is called LII Citer (link here) and it is offered by the Cornell Legal Information Institute. The tool works by adding the Citer to your favorites (in any browser). Simply highlight the law on the web page, then go to the Citer link in your Favorites and you will see the text of the highlighted statute. It currently accesses federal law only, see the list below:

  • U.S. Code, e.g. 12 U.S.C. 1749bbb-10c, or 7 U.S.C. 136a(c)(3), which links to the paragraph level, using the LII internal USC resolver.
  • United States Supreme Court, e.g. 457 U.S. 800, using the LII resolver that tries to find an LII-local copy, and failing that, gives the user the option of choosing another source.
  • Federal Circuit Court System, e.g. 875 F.2d 1059, “resolved” by constructing a direct link to the resource.org data set as hosted by lawlibrary.rutgers.edu
  • Code of Federal Regulations, e.g. 40 C.F.R. Part 164 Subpart D, tries to resolve section references with the get-cfr.cgi file at frwebgate.access.gpo.gov; if no section number is cited, then a resolver at ecfr.gpoaccess.gov is used.
  • US Statutes at Large, e.g. 118 Stat. 919, resolution currently very speculative, using get-cfr.cgi at frwebgate.access.gpo.gov
  • US Public Law, e.g. Pub. L. 110-116, fairly stable, using get-cfr.cgi at frwebgate.access.gpo.gov
  • Federal Register, e.g. 72 Fed. Reg. 37771, uses the getpage.cgi at frwebgate.access.gpo.gov

Even without state statutes, it is still a handy tool for speeding up your web-based research process. Thanks Cornell and RIPS!

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Your Stimulus Dollars at Work: Tightening Up Search

Imagine a search engine that employs experiments to learn from you? The computer scientists at Cornell University have and they are using stimulus money (a four-year, $1 million grant) to improve search based on such experiments. The scientists are looking to develop search engine software that can read your queries and clicks, as well as subsequent query reformulations, in order to understand search methodology and what does and doesn’t work. The software developed from these efforts will be best used in specialized collections – the examples from the press release include scientific and legal collections and corporate intranets.

The search engine software will learn what works best by analyzing user data, almost as if by osmosis. The researchers already have developed the aptly-named Osmot and are looking to improve the process by tightening the experimental controls. More on Osmot at this link.

What does it all mean for you? Smarter search engines might yield faster and better results, but I still hesitate slightly at the thought of a machine’s judgment regarding what is and is not relevant substituting for my own. In any event, it will be interesting to see where this inqury leads and the ramifications for search.